theblackcat102
commited on
Commit
•
afd3781
1
Parent(s):
532af29
Upload 6 files
Browse files- config.json +25 -0
- pytorch_model.bin.index.json +551 -0
- special_tokens_map.json +13 -0
- tokenizer.json +0 -0
- tokenizer_config.json +10 -0
- trainer_state.json +1804 -0
config.json
ADDED
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "EleutherAI/pythia-12b-deduped",
|
3 |
+
"architectures": [
|
4 |
+
"GPTNeoXForCausalLM"
|
5 |
+
],
|
6 |
+
"bos_token_id": 0,
|
7 |
+
"eos_token_id": 0,
|
8 |
+
"hidden_act": "gelu",
|
9 |
+
"hidden_size": 5120,
|
10 |
+
"initializer_range": 0.02,
|
11 |
+
"intermediate_size": 20480,
|
12 |
+
"layer_norm_eps": 1e-05,
|
13 |
+
"max_position_embeddings": 2048,
|
14 |
+
"model_type": "gpt_neox",
|
15 |
+
"num_attention_heads": 40,
|
16 |
+
"num_hidden_layers": 36,
|
17 |
+
"rotary_emb_base": 10000,
|
18 |
+
"rotary_pct": 0.25,
|
19 |
+
"tie_word_embeddings": false,
|
20 |
+
"torch_dtype": "float16",
|
21 |
+
"transformers_version": "4.25.1",
|
22 |
+
"use_cache": true,
|
23 |
+
"use_parallel_residual": true,
|
24 |
+
"vocab_size": 50281
|
25 |
+
}
|
pytorch_model.bin.index.json
ADDED
@@ -0,0 +1,551 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"metadata": {
|
3 |
+
"total_size": 23834805448
|
4 |
+
},
|
5 |
+
"weight_map": {
|
6 |
+
"embed_out.weight": "pytorch_model-00003-of-00003.bin",
|
7 |
+
"gpt_neox.embed_in.weight": "pytorch_model-00001-of-00003.bin",
|
8 |
+
"gpt_neox.final_layer_norm.bias": "pytorch_model-00003-of-00003.bin",
|
9 |
+
"gpt_neox.final_layer_norm.weight": "pytorch_model-00003-of-00003.bin",
|
10 |
+
"gpt_neox.layers.0.attention.bias": "pytorch_model-00001-of-00003.bin",
|
11 |
+
"gpt_neox.layers.0.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
12 |
+
"gpt_neox.layers.0.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
13 |
+
"gpt_neox.layers.0.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
14 |
+
"gpt_neox.layers.0.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
15 |
+
"gpt_neox.layers.0.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
16 |
+
"gpt_neox.layers.0.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
17 |
+
"gpt_neox.layers.0.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
18 |
+
"gpt_neox.layers.0.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
19 |
+
"gpt_neox.layers.0.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
20 |
+
"gpt_neox.layers.0.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
21 |
+
"gpt_neox.layers.0.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
22 |
+
"gpt_neox.layers.0.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
23 |
+
"gpt_neox.layers.0.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
24 |
+
"gpt_neox.layers.0.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
25 |
+
"gpt_neox.layers.1.attention.bias": "pytorch_model-00001-of-00003.bin",
|
26 |
+
"gpt_neox.layers.1.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
27 |
+
"gpt_neox.layers.1.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
28 |
+
"gpt_neox.layers.1.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
29 |
+
"gpt_neox.layers.1.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
30 |
+
"gpt_neox.layers.1.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
31 |
+
"gpt_neox.layers.1.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
32 |
+
"gpt_neox.layers.1.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
33 |
+
"gpt_neox.layers.1.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
34 |
+
"gpt_neox.layers.1.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
35 |
+
"gpt_neox.layers.1.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
36 |
+
"gpt_neox.layers.1.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
37 |
+
"gpt_neox.layers.1.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
38 |
+
"gpt_neox.layers.1.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
39 |
+
"gpt_neox.layers.1.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
40 |
+
"gpt_neox.layers.10.attention.bias": "pytorch_model-00001-of-00003.bin",
|
41 |
+
"gpt_neox.layers.10.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
42 |
+
"gpt_neox.layers.10.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
43 |
+
"gpt_neox.layers.10.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
44 |
+
"gpt_neox.layers.10.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
45 |
+
"gpt_neox.layers.10.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
46 |
+
"gpt_neox.layers.10.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
47 |
+
"gpt_neox.layers.10.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
48 |
+
"gpt_neox.layers.10.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
49 |
+
"gpt_neox.layers.10.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
50 |
+
"gpt_neox.layers.10.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
51 |
+
"gpt_neox.layers.10.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
52 |
+
"gpt_neox.layers.10.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
53 |
+
"gpt_neox.layers.10.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
54 |
+
"gpt_neox.layers.10.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
55 |
+
"gpt_neox.layers.11.attention.bias": "pytorch_model-00001-of-00003.bin",
|
56 |
+
"gpt_neox.layers.11.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
57 |
+
"gpt_neox.layers.11.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
58 |
+
"gpt_neox.layers.11.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
59 |
+
"gpt_neox.layers.11.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
60 |
+
"gpt_neox.layers.11.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
61 |
+
"gpt_neox.layers.11.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
62 |
+
"gpt_neox.layers.11.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
63 |
+
"gpt_neox.layers.11.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
64 |
+
"gpt_neox.layers.11.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
65 |
+
"gpt_neox.layers.11.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
66 |
+
"gpt_neox.layers.11.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
67 |
+
"gpt_neox.layers.11.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
68 |
+
"gpt_neox.layers.11.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
69 |
+
"gpt_neox.layers.11.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
70 |
+
"gpt_neox.layers.12.attention.bias": "pytorch_model-00001-of-00003.bin",
|
71 |
+
"gpt_neox.layers.12.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
72 |
+
"gpt_neox.layers.12.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
73 |
+
"gpt_neox.layers.12.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
74 |
+
"gpt_neox.layers.12.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
75 |
+
"gpt_neox.layers.12.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
76 |
+
"gpt_neox.layers.12.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
77 |
+
"gpt_neox.layers.12.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
78 |
+
"gpt_neox.layers.12.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
79 |
+
"gpt_neox.layers.12.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
80 |
+
"gpt_neox.layers.12.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
81 |
+
"gpt_neox.layers.12.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
82 |
+
"gpt_neox.layers.12.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
83 |
+
"gpt_neox.layers.12.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
84 |
+
"gpt_neox.layers.12.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
85 |
+
"gpt_neox.layers.13.attention.bias": "pytorch_model-00001-of-00003.bin",
|
86 |
+
"gpt_neox.layers.13.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
87 |
+
"gpt_neox.layers.13.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
88 |
+
"gpt_neox.layers.13.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
89 |
+
"gpt_neox.layers.13.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
90 |
+
"gpt_neox.layers.13.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
91 |
+
"gpt_neox.layers.13.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
92 |
+
"gpt_neox.layers.13.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
93 |
+
"gpt_neox.layers.13.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
94 |
+
"gpt_neox.layers.13.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
95 |
+
"gpt_neox.layers.13.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
96 |
+
"gpt_neox.layers.13.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
97 |
+
"gpt_neox.layers.13.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
98 |
+
"gpt_neox.layers.13.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
99 |
+
"gpt_neox.layers.13.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
100 |
+
"gpt_neox.layers.14.attention.bias": "pytorch_model-00001-of-00003.bin",
|
101 |
+
"gpt_neox.layers.14.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
102 |
+
"gpt_neox.layers.14.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
103 |
+
"gpt_neox.layers.14.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
104 |
+
"gpt_neox.layers.14.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
105 |
+
"gpt_neox.layers.14.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
106 |
+
"gpt_neox.layers.14.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
107 |
+
"gpt_neox.layers.14.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
108 |
+
"gpt_neox.layers.14.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
109 |
+
"gpt_neox.layers.14.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
110 |
+
"gpt_neox.layers.14.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
111 |
+
"gpt_neox.layers.14.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
112 |
+
"gpt_neox.layers.14.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
113 |
+
"gpt_neox.layers.14.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
114 |
+
"gpt_neox.layers.14.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
115 |
+
"gpt_neox.layers.15.attention.bias": "pytorch_model-00002-of-00003.bin",
|
116 |
+
"gpt_neox.layers.15.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
117 |
+
"gpt_neox.layers.15.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
118 |
+
"gpt_neox.layers.15.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
119 |
+
"gpt_neox.layers.15.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
120 |
+
"gpt_neox.layers.15.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
121 |
+
"gpt_neox.layers.15.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
122 |
+
"gpt_neox.layers.15.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
123 |
+
"gpt_neox.layers.15.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
124 |
+
"gpt_neox.layers.15.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
125 |
+
"gpt_neox.layers.15.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
126 |
+
"gpt_neox.layers.15.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
127 |
+
"gpt_neox.layers.15.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
128 |
+
"gpt_neox.layers.15.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
129 |
+
"gpt_neox.layers.15.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
130 |
+
"gpt_neox.layers.16.attention.bias": "pytorch_model-00002-of-00003.bin",
|
131 |
+
"gpt_neox.layers.16.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
132 |
+
"gpt_neox.layers.16.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
133 |
+
"gpt_neox.layers.16.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
134 |
+
"gpt_neox.layers.16.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
135 |
+
"gpt_neox.layers.16.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
136 |
+
"gpt_neox.layers.16.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
137 |
+
"gpt_neox.layers.16.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
138 |
+
"gpt_neox.layers.16.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
139 |
+
"gpt_neox.layers.16.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
140 |
+
"gpt_neox.layers.16.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
141 |
+
"gpt_neox.layers.16.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
142 |
+
"gpt_neox.layers.16.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
143 |
+
"gpt_neox.layers.16.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
144 |
+
"gpt_neox.layers.16.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
145 |
+
"gpt_neox.layers.17.attention.bias": "pytorch_model-00002-of-00003.bin",
|
146 |
+
"gpt_neox.layers.17.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
147 |
+
"gpt_neox.layers.17.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
148 |
+
"gpt_neox.layers.17.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
149 |
+
"gpt_neox.layers.17.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
150 |
+
"gpt_neox.layers.17.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
151 |
+
"gpt_neox.layers.17.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
152 |
+
"gpt_neox.layers.17.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
153 |
+
"gpt_neox.layers.17.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
154 |
+
"gpt_neox.layers.17.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
155 |
+
"gpt_neox.layers.17.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
156 |
+
"gpt_neox.layers.17.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
157 |
+
"gpt_neox.layers.17.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
158 |
+
"gpt_neox.layers.17.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
159 |
+
"gpt_neox.layers.17.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
160 |
+
"gpt_neox.layers.18.attention.bias": "pytorch_model-00002-of-00003.bin",
|
161 |
+
"gpt_neox.layers.18.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
162 |
+
"gpt_neox.layers.18.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
163 |
+
"gpt_neox.layers.18.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
164 |
+
"gpt_neox.layers.18.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
165 |
+
"gpt_neox.layers.18.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
166 |
+
"gpt_neox.layers.18.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
167 |
+
"gpt_neox.layers.18.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
168 |
+
"gpt_neox.layers.18.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
169 |
+
"gpt_neox.layers.18.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
170 |
+
"gpt_neox.layers.18.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
171 |
+
"gpt_neox.layers.18.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
172 |
+
"gpt_neox.layers.18.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
173 |
+
"gpt_neox.layers.18.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
174 |
+
"gpt_neox.layers.18.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
175 |
+
"gpt_neox.layers.19.attention.bias": "pytorch_model-00002-of-00003.bin",
|
176 |
+
"gpt_neox.layers.19.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
177 |
+
"gpt_neox.layers.19.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
178 |
+
"gpt_neox.layers.19.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
179 |
+
"gpt_neox.layers.19.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
180 |
+
"gpt_neox.layers.19.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
181 |
+
"gpt_neox.layers.19.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
182 |
+
"gpt_neox.layers.19.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
183 |
+
"gpt_neox.layers.19.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
184 |
+
"gpt_neox.layers.19.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
185 |
+
"gpt_neox.layers.19.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
186 |
+
"gpt_neox.layers.19.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
187 |
+
"gpt_neox.layers.19.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
188 |
+
"gpt_neox.layers.19.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
189 |
+
"gpt_neox.layers.19.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
190 |
+
"gpt_neox.layers.2.attention.bias": "pytorch_model-00001-of-00003.bin",
|
191 |
+
"gpt_neox.layers.2.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
192 |
+
"gpt_neox.layers.2.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
193 |
+
"gpt_neox.layers.2.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
194 |
+
"gpt_neox.layers.2.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
195 |
+
"gpt_neox.layers.2.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
196 |
+
"gpt_neox.layers.2.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
197 |
+
"gpt_neox.layers.2.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
198 |
+
"gpt_neox.layers.2.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
199 |
+
"gpt_neox.layers.2.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
200 |
+
"gpt_neox.layers.2.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
201 |
+
"gpt_neox.layers.2.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
202 |
+
"gpt_neox.layers.2.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
203 |
+
"gpt_neox.layers.2.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
204 |
+
"gpt_neox.layers.2.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
205 |
+
"gpt_neox.layers.20.attention.bias": "pytorch_model-00002-of-00003.bin",
|
206 |
+
"gpt_neox.layers.20.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
207 |
+
"gpt_neox.layers.20.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
208 |
+
"gpt_neox.layers.20.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
209 |
+
"gpt_neox.layers.20.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
210 |
+
"gpt_neox.layers.20.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
211 |
+
"gpt_neox.layers.20.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
212 |
+
"gpt_neox.layers.20.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
213 |
+
"gpt_neox.layers.20.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
214 |
+
"gpt_neox.layers.20.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
215 |
+
"gpt_neox.layers.20.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
216 |
+
"gpt_neox.layers.20.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
217 |
+
"gpt_neox.layers.20.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
218 |
+
"gpt_neox.layers.20.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
219 |
+
"gpt_neox.layers.20.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
220 |
+
"gpt_neox.layers.21.attention.bias": "pytorch_model-00002-of-00003.bin",
|
221 |
+
"gpt_neox.layers.21.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
222 |
+
"gpt_neox.layers.21.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
223 |
+
"gpt_neox.layers.21.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
224 |
+
"gpt_neox.layers.21.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
225 |
+
"gpt_neox.layers.21.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
226 |
+
"gpt_neox.layers.21.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
227 |
+
"gpt_neox.layers.21.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
228 |
+
"gpt_neox.layers.21.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
229 |
+
"gpt_neox.layers.21.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
230 |
+
"gpt_neox.layers.21.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
231 |
+
"gpt_neox.layers.21.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
232 |
+
"gpt_neox.layers.21.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
233 |
+
"gpt_neox.layers.21.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
234 |
+
"gpt_neox.layers.21.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
235 |
+
"gpt_neox.layers.22.attention.bias": "pytorch_model-00002-of-00003.bin",
|
236 |
+
"gpt_neox.layers.22.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
237 |
+
"gpt_neox.layers.22.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
238 |
+
"gpt_neox.layers.22.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
239 |
+
"gpt_neox.layers.22.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
240 |
+
"gpt_neox.layers.22.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
241 |
+
"gpt_neox.layers.22.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
242 |
+
"gpt_neox.layers.22.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
243 |
+
"gpt_neox.layers.22.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
244 |
+
"gpt_neox.layers.22.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
245 |
+
"gpt_neox.layers.22.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
246 |
+
"gpt_neox.layers.22.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
247 |
+
"gpt_neox.layers.22.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
248 |
+
"gpt_neox.layers.22.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
249 |
+
"gpt_neox.layers.22.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
250 |
+
"gpt_neox.layers.23.attention.bias": "pytorch_model-00002-of-00003.bin",
|
251 |
+
"gpt_neox.layers.23.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
252 |
+
"gpt_neox.layers.23.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
253 |
+
"gpt_neox.layers.23.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
254 |
+
"gpt_neox.layers.23.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
255 |
+
"gpt_neox.layers.23.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
256 |
+
"gpt_neox.layers.23.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
257 |
+
"gpt_neox.layers.23.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
258 |
+
"gpt_neox.layers.23.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
259 |
+
"gpt_neox.layers.23.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
260 |
+
"gpt_neox.layers.23.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
261 |
+
"gpt_neox.layers.23.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
262 |
+
"gpt_neox.layers.23.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
263 |
+
"gpt_neox.layers.23.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
264 |
+
"gpt_neox.layers.23.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
265 |
+
"gpt_neox.layers.24.attention.bias": "pytorch_model-00002-of-00003.bin",
|
266 |
+
"gpt_neox.layers.24.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
267 |
+
"gpt_neox.layers.24.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
268 |
+
"gpt_neox.layers.24.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
269 |
+
"gpt_neox.layers.24.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
270 |
+
"gpt_neox.layers.24.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
271 |
+
"gpt_neox.layers.24.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
272 |
+
"gpt_neox.layers.24.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
273 |
+
"gpt_neox.layers.24.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
274 |
+
"gpt_neox.layers.24.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
275 |
+
"gpt_neox.layers.24.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
276 |
+
"gpt_neox.layers.24.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
277 |
+
"gpt_neox.layers.24.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
278 |
+
"gpt_neox.layers.24.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
279 |
+
"gpt_neox.layers.24.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
280 |
+
"gpt_neox.layers.25.attention.bias": "pytorch_model-00002-of-00003.bin",
|
281 |
+
"gpt_neox.layers.25.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
282 |
+
"gpt_neox.layers.25.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
283 |
+
"gpt_neox.layers.25.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
284 |
+
"gpt_neox.layers.25.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
285 |
+
"gpt_neox.layers.25.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
286 |
+
"gpt_neox.layers.25.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
287 |
+
"gpt_neox.layers.25.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
288 |
+
"gpt_neox.layers.25.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
289 |
+
"gpt_neox.layers.25.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
290 |
+
"gpt_neox.layers.25.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
291 |
+
"gpt_neox.layers.25.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
292 |
+
"gpt_neox.layers.25.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
293 |
+
"gpt_neox.layers.25.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
294 |
+
"gpt_neox.layers.25.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
295 |
+
"gpt_neox.layers.26.attention.bias": "pytorch_model-00002-of-00003.bin",
|
296 |
+
"gpt_neox.layers.26.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
297 |
+
"gpt_neox.layers.26.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
298 |
+
"gpt_neox.layers.26.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
299 |
+
"gpt_neox.layers.26.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
300 |
+
"gpt_neox.layers.26.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
301 |
+
"gpt_neox.layers.26.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
302 |
+
"gpt_neox.layers.26.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
303 |
+
"gpt_neox.layers.26.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
304 |
+
"gpt_neox.layers.26.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
305 |
+
"gpt_neox.layers.26.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
306 |
+
"gpt_neox.layers.26.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
307 |
+
"gpt_neox.layers.26.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
308 |
+
"gpt_neox.layers.26.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
309 |
+
"gpt_neox.layers.26.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
310 |
+
"gpt_neox.layers.27.attention.bias": "pytorch_model-00002-of-00003.bin",
|
311 |
+
"gpt_neox.layers.27.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
312 |
+
"gpt_neox.layers.27.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
313 |
+
"gpt_neox.layers.27.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
314 |
+
"gpt_neox.layers.27.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
315 |
+
"gpt_neox.layers.27.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
316 |
+
"gpt_neox.layers.27.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
317 |
+
"gpt_neox.layers.27.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
318 |
+
"gpt_neox.layers.27.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
319 |
+
"gpt_neox.layers.27.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
320 |
+
"gpt_neox.layers.27.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
321 |
+
"gpt_neox.layers.27.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
322 |
+
"gpt_neox.layers.27.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
323 |
+
"gpt_neox.layers.27.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
324 |
+
"gpt_neox.layers.27.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
325 |
+
"gpt_neox.layers.28.attention.bias": "pytorch_model-00002-of-00003.bin",
|
326 |
+
"gpt_neox.layers.28.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
327 |
+
"gpt_neox.layers.28.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
328 |
+
"gpt_neox.layers.28.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
329 |
+
"gpt_neox.layers.28.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
330 |
+
"gpt_neox.layers.28.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
331 |
+
"gpt_neox.layers.28.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
332 |
+
"gpt_neox.layers.28.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
333 |
+
"gpt_neox.layers.28.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
334 |
+
"gpt_neox.layers.28.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
335 |
+
"gpt_neox.layers.28.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
336 |
+
"gpt_neox.layers.28.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
337 |
+
"gpt_neox.layers.28.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
338 |
+
"gpt_neox.layers.28.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
339 |
+
"gpt_neox.layers.28.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
340 |
+
"gpt_neox.layers.29.attention.bias": "pytorch_model-00002-of-00003.bin",
|
341 |
+
"gpt_neox.layers.29.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
342 |
+
"gpt_neox.layers.29.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
343 |
+
"gpt_neox.layers.29.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
344 |
+
"gpt_neox.layers.29.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
345 |
+
"gpt_neox.layers.29.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
346 |
+
"gpt_neox.layers.29.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
347 |
+
"gpt_neox.layers.29.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
348 |
+
"gpt_neox.layers.29.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
349 |
+
"gpt_neox.layers.29.mlp.dense_4h_to_h.bias": "pytorch_model-00002-of-00003.bin",
|
350 |
+
"gpt_neox.layers.29.mlp.dense_4h_to_h.weight": "pytorch_model-00002-of-00003.bin",
|
351 |
+
"gpt_neox.layers.29.mlp.dense_h_to_4h.bias": "pytorch_model-00002-of-00003.bin",
|
352 |
+
"gpt_neox.layers.29.mlp.dense_h_to_4h.weight": "pytorch_model-00002-of-00003.bin",
|
353 |
+
"gpt_neox.layers.29.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
354 |
+
"gpt_neox.layers.29.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
355 |
+
"gpt_neox.layers.3.attention.bias": "pytorch_model-00001-of-00003.bin",
|
356 |
+
"gpt_neox.layers.3.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
357 |
+
"gpt_neox.layers.3.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
358 |
+
"gpt_neox.layers.3.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
359 |
+
"gpt_neox.layers.3.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
360 |
+
"gpt_neox.layers.3.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
361 |
+
"gpt_neox.layers.3.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
362 |
+
"gpt_neox.layers.3.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
363 |
+
"gpt_neox.layers.3.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
364 |
+
"gpt_neox.layers.3.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
365 |
+
"gpt_neox.layers.3.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
366 |
+
"gpt_neox.layers.3.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
367 |
+
"gpt_neox.layers.3.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
368 |
+
"gpt_neox.layers.3.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
369 |
+
"gpt_neox.layers.3.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
370 |
+
"gpt_neox.layers.30.attention.bias": "pytorch_model-00002-of-00003.bin",
|
371 |
+
"gpt_neox.layers.30.attention.dense.bias": "pytorch_model-00002-of-00003.bin",
|
372 |
+
"gpt_neox.layers.30.attention.dense.weight": "pytorch_model-00002-of-00003.bin",
|
373 |
+
"gpt_neox.layers.30.attention.masked_bias": "pytorch_model-00002-of-00003.bin",
|
374 |
+
"gpt_neox.layers.30.attention.query_key_value.bias": "pytorch_model-00002-of-00003.bin",
|
375 |
+
"gpt_neox.layers.30.attention.query_key_value.weight": "pytorch_model-00002-of-00003.bin",
|
376 |
+
"gpt_neox.layers.30.attention.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin",
|
377 |
+
"gpt_neox.layers.30.input_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
378 |
+
"gpt_neox.layers.30.input_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
379 |
+
"gpt_neox.layers.30.mlp.dense_4h_to_h.bias": "pytorch_model-00003-of-00003.bin",
|
380 |
+
"gpt_neox.layers.30.mlp.dense_4h_to_h.weight": "pytorch_model-00003-of-00003.bin",
|
381 |
+
"gpt_neox.layers.30.mlp.dense_h_to_4h.bias": "pytorch_model-00003-of-00003.bin",
|
382 |
+
"gpt_neox.layers.30.mlp.dense_h_to_4h.weight": "pytorch_model-00003-of-00003.bin",
|
383 |
+
"gpt_neox.layers.30.post_attention_layernorm.bias": "pytorch_model-00002-of-00003.bin",
|
384 |
+
"gpt_neox.layers.30.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin",
|
385 |
+
"gpt_neox.layers.31.attention.bias": "pytorch_model-00003-of-00003.bin",
|
386 |
+
"gpt_neox.layers.31.attention.dense.bias": "pytorch_model-00003-of-00003.bin",
|
387 |
+
"gpt_neox.layers.31.attention.dense.weight": "pytorch_model-00003-of-00003.bin",
|
388 |
+
"gpt_neox.layers.31.attention.masked_bias": "pytorch_model-00003-of-00003.bin",
|
389 |
+
"gpt_neox.layers.31.attention.query_key_value.bias": "pytorch_model-00003-of-00003.bin",
|
390 |
+
"gpt_neox.layers.31.attention.query_key_value.weight": "pytorch_model-00003-of-00003.bin",
|
391 |
+
"gpt_neox.layers.31.attention.rotary_emb.inv_freq": "pytorch_model-00003-of-00003.bin",
|
392 |
+
"gpt_neox.layers.31.input_layernorm.bias": "pytorch_model-00003-of-00003.bin",
|
393 |
+
"gpt_neox.layers.31.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
|
394 |
+
"gpt_neox.layers.31.mlp.dense_4h_to_h.bias": "pytorch_model-00003-of-00003.bin",
|
395 |
+
"gpt_neox.layers.31.mlp.dense_4h_to_h.weight": "pytorch_model-00003-of-00003.bin",
|
396 |
+
"gpt_neox.layers.31.mlp.dense_h_to_4h.bias": "pytorch_model-00003-of-00003.bin",
|
397 |
+
"gpt_neox.layers.31.mlp.dense_h_to_4h.weight": "pytorch_model-00003-of-00003.bin",
|
398 |
+
"gpt_neox.layers.31.post_attention_layernorm.bias": "pytorch_model-00003-of-00003.bin",
|
399 |
+
"gpt_neox.layers.31.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
|
400 |
+
"gpt_neox.layers.32.attention.bias": "pytorch_model-00003-of-00003.bin",
|
401 |
+
"gpt_neox.layers.32.attention.dense.bias": "pytorch_model-00003-of-00003.bin",
|
402 |
+
"gpt_neox.layers.32.attention.dense.weight": "pytorch_model-00003-of-00003.bin",
|
403 |
+
"gpt_neox.layers.32.attention.masked_bias": "pytorch_model-00003-of-00003.bin",
|
404 |
+
"gpt_neox.layers.32.attention.query_key_value.bias": "pytorch_model-00003-of-00003.bin",
|
405 |
+
"gpt_neox.layers.32.attention.query_key_value.weight": "pytorch_model-00003-of-00003.bin",
|
406 |
+
"gpt_neox.layers.32.attention.rotary_emb.inv_freq": "pytorch_model-00003-of-00003.bin",
|
407 |
+
"gpt_neox.layers.32.input_layernorm.bias": "pytorch_model-00003-of-00003.bin",
|
408 |
+
"gpt_neox.layers.32.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
|
409 |
+
"gpt_neox.layers.32.mlp.dense_4h_to_h.bias": "pytorch_model-00003-of-00003.bin",
|
410 |
+
"gpt_neox.layers.32.mlp.dense_4h_to_h.weight": "pytorch_model-00003-of-00003.bin",
|
411 |
+
"gpt_neox.layers.32.mlp.dense_h_to_4h.bias": "pytorch_model-00003-of-00003.bin",
|
412 |
+
"gpt_neox.layers.32.mlp.dense_h_to_4h.weight": "pytorch_model-00003-of-00003.bin",
|
413 |
+
"gpt_neox.layers.32.post_attention_layernorm.bias": "pytorch_model-00003-of-00003.bin",
|
414 |
+
"gpt_neox.layers.32.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
|
415 |
+
"gpt_neox.layers.33.attention.bias": "pytorch_model-00003-of-00003.bin",
|
416 |
+
"gpt_neox.layers.33.attention.dense.bias": "pytorch_model-00003-of-00003.bin",
|
417 |
+
"gpt_neox.layers.33.attention.dense.weight": "pytorch_model-00003-of-00003.bin",
|
418 |
+
"gpt_neox.layers.33.attention.masked_bias": "pytorch_model-00003-of-00003.bin",
|
419 |
+
"gpt_neox.layers.33.attention.query_key_value.bias": "pytorch_model-00003-of-00003.bin",
|
420 |
+
"gpt_neox.layers.33.attention.query_key_value.weight": "pytorch_model-00003-of-00003.bin",
|
421 |
+
"gpt_neox.layers.33.attention.rotary_emb.inv_freq": "pytorch_model-00003-of-00003.bin",
|
422 |
+
"gpt_neox.layers.33.input_layernorm.bias": "pytorch_model-00003-of-00003.bin",
|
423 |
+
"gpt_neox.layers.33.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
|
424 |
+
"gpt_neox.layers.33.mlp.dense_4h_to_h.bias": "pytorch_model-00003-of-00003.bin",
|
425 |
+
"gpt_neox.layers.33.mlp.dense_4h_to_h.weight": "pytorch_model-00003-of-00003.bin",
|
426 |
+
"gpt_neox.layers.33.mlp.dense_h_to_4h.bias": "pytorch_model-00003-of-00003.bin",
|
427 |
+
"gpt_neox.layers.33.mlp.dense_h_to_4h.weight": "pytorch_model-00003-of-00003.bin",
|
428 |
+
"gpt_neox.layers.33.post_attention_layernorm.bias": "pytorch_model-00003-of-00003.bin",
|
429 |
+
"gpt_neox.layers.33.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
|
430 |
+
"gpt_neox.layers.34.attention.bias": "pytorch_model-00003-of-00003.bin",
|
431 |
+
"gpt_neox.layers.34.attention.dense.bias": "pytorch_model-00003-of-00003.bin",
|
432 |
+
"gpt_neox.layers.34.attention.dense.weight": "pytorch_model-00003-of-00003.bin",
|
433 |
+
"gpt_neox.layers.34.attention.masked_bias": "pytorch_model-00003-of-00003.bin",
|
434 |
+
"gpt_neox.layers.34.attention.query_key_value.bias": "pytorch_model-00003-of-00003.bin",
|
435 |
+
"gpt_neox.layers.34.attention.query_key_value.weight": "pytorch_model-00003-of-00003.bin",
|
436 |
+
"gpt_neox.layers.34.attention.rotary_emb.inv_freq": "pytorch_model-00003-of-00003.bin",
|
437 |
+
"gpt_neox.layers.34.input_layernorm.bias": "pytorch_model-00003-of-00003.bin",
|
438 |
+
"gpt_neox.layers.34.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
|
439 |
+
"gpt_neox.layers.34.mlp.dense_4h_to_h.bias": "pytorch_model-00003-of-00003.bin",
|
440 |
+
"gpt_neox.layers.34.mlp.dense_4h_to_h.weight": "pytorch_model-00003-of-00003.bin",
|
441 |
+
"gpt_neox.layers.34.mlp.dense_h_to_4h.bias": "pytorch_model-00003-of-00003.bin",
|
442 |
+
"gpt_neox.layers.34.mlp.dense_h_to_4h.weight": "pytorch_model-00003-of-00003.bin",
|
443 |
+
"gpt_neox.layers.34.post_attention_layernorm.bias": "pytorch_model-00003-of-00003.bin",
|
444 |
+
"gpt_neox.layers.34.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
|
445 |
+
"gpt_neox.layers.35.attention.bias": "pytorch_model-00003-of-00003.bin",
|
446 |
+
"gpt_neox.layers.35.attention.dense.bias": "pytorch_model-00003-of-00003.bin",
|
447 |
+
"gpt_neox.layers.35.attention.dense.weight": "pytorch_model-00003-of-00003.bin",
|
448 |
+
"gpt_neox.layers.35.attention.masked_bias": "pytorch_model-00003-of-00003.bin",
|
449 |
+
"gpt_neox.layers.35.attention.query_key_value.bias": "pytorch_model-00003-of-00003.bin",
|
450 |
+
"gpt_neox.layers.35.attention.query_key_value.weight": "pytorch_model-00003-of-00003.bin",
|
451 |
+
"gpt_neox.layers.35.attention.rotary_emb.inv_freq": "pytorch_model-00003-of-00003.bin",
|
452 |
+
"gpt_neox.layers.35.input_layernorm.bias": "pytorch_model-00003-of-00003.bin",
|
453 |
+
"gpt_neox.layers.35.input_layernorm.weight": "pytorch_model-00003-of-00003.bin",
|
454 |
+
"gpt_neox.layers.35.mlp.dense_4h_to_h.bias": "pytorch_model-00003-of-00003.bin",
|
455 |
+
"gpt_neox.layers.35.mlp.dense_4h_to_h.weight": "pytorch_model-00003-of-00003.bin",
|
456 |
+
"gpt_neox.layers.35.mlp.dense_h_to_4h.bias": "pytorch_model-00003-of-00003.bin",
|
457 |
+
"gpt_neox.layers.35.mlp.dense_h_to_4h.weight": "pytorch_model-00003-of-00003.bin",
|
458 |
+
"gpt_neox.layers.35.post_attention_layernorm.bias": "pytorch_model-00003-of-00003.bin",
|
459 |
+
"gpt_neox.layers.35.post_attention_layernorm.weight": "pytorch_model-00003-of-00003.bin",
|
460 |
+
"gpt_neox.layers.4.attention.bias": "pytorch_model-00001-of-00003.bin",
|
461 |
+
"gpt_neox.layers.4.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
462 |
+
"gpt_neox.layers.4.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
463 |
+
"gpt_neox.layers.4.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
464 |
+
"gpt_neox.layers.4.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
465 |
+
"gpt_neox.layers.4.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
466 |
+
"gpt_neox.layers.4.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
467 |
+
"gpt_neox.layers.4.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
468 |
+
"gpt_neox.layers.4.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
469 |
+
"gpt_neox.layers.4.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
470 |
+
"gpt_neox.layers.4.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
471 |
+
"gpt_neox.layers.4.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
472 |
+
"gpt_neox.layers.4.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
473 |
+
"gpt_neox.layers.4.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
474 |
+
"gpt_neox.layers.4.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
475 |
+
"gpt_neox.layers.5.attention.bias": "pytorch_model-00001-of-00003.bin",
|
476 |
+
"gpt_neox.layers.5.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
477 |
+
"gpt_neox.layers.5.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
478 |
+
"gpt_neox.layers.5.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
479 |
+
"gpt_neox.layers.5.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
480 |
+
"gpt_neox.layers.5.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
481 |
+
"gpt_neox.layers.5.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
482 |
+
"gpt_neox.layers.5.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
483 |
+
"gpt_neox.layers.5.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
484 |
+
"gpt_neox.layers.5.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
485 |
+
"gpt_neox.layers.5.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
486 |
+
"gpt_neox.layers.5.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
487 |
+
"gpt_neox.layers.5.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
488 |
+
"gpt_neox.layers.5.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
489 |
+
"gpt_neox.layers.5.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
490 |
+
"gpt_neox.layers.6.attention.bias": "pytorch_model-00001-of-00003.bin",
|
491 |
+
"gpt_neox.layers.6.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
492 |
+
"gpt_neox.layers.6.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
493 |
+
"gpt_neox.layers.6.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
494 |
+
"gpt_neox.layers.6.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
495 |
+
"gpt_neox.layers.6.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
496 |
+
"gpt_neox.layers.6.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
497 |
+
"gpt_neox.layers.6.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
498 |
+
"gpt_neox.layers.6.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
499 |
+
"gpt_neox.layers.6.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
500 |
+
"gpt_neox.layers.6.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
501 |
+
"gpt_neox.layers.6.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
502 |
+
"gpt_neox.layers.6.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
503 |
+
"gpt_neox.layers.6.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
504 |
+
"gpt_neox.layers.6.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
505 |
+
"gpt_neox.layers.7.attention.bias": "pytorch_model-00001-of-00003.bin",
|
506 |
+
"gpt_neox.layers.7.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
507 |
+
"gpt_neox.layers.7.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
508 |
+
"gpt_neox.layers.7.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
509 |
+
"gpt_neox.layers.7.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
510 |
+
"gpt_neox.layers.7.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
511 |
+
"gpt_neox.layers.7.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
512 |
+
"gpt_neox.layers.7.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
513 |
+
"gpt_neox.layers.7.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
514 |
+
"gpt_neox.layers.7.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
515 |
+
"gpt_neox.layers.7.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
516 |
+
"gpt_neox.layers.7.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
517 |
+
"gpt_neox.layers.7.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
518 |
+
"gpt_neox.layers.7.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
519 |
+
"gpt_neox.layers.7.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
520 |
+
"gpt_neox.layers.8.attention.bias": "pytorch_model-00001-of-00003.bin",
|
521 |
+
"gpt_neox.layers.8.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
522 |
+
"gpt_neox.layers.8.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
523 |
+
"gpt_neox.layers.8.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
524 |
+
"gpt_neox.layers.8.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
525 |
+
"gpt_neox.layers.8.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
526 |
+
"gpt_neox.layers.8.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
527 |
+
"gpt_neox.layers.8.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
528 |
+
"gpt_neox.layers.8.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
529 |
+
"gpt_neox.layers.8.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
530 |
+
"gpt_neox.layers.8.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
531 |
+
"gpt_neox.layers.8.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
532 |
+
"gpt_neox.layers.8.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
533 |
+
"gpt_neox.layers.8.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
534 |
+
"gpt_neox.layers.8.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
535 |
+
"gpt_neox.layers.9.attention.bias": "pytorch_model-00001-of-00003.bin",
|
536 |
+
"gpt_neox.layers.9.attention.dense.bias": "pytorch_model-00001-of-00003.bin",
|
537 |
+
"gpt_neox.layers.9.attention.dense.weight": "pytorch_model-00001-of-00003.bin",
|
538 |
+
"gpt_neox.layers.9.attention.masked_bias": "pytorch_model-00001-of-00003.bin",
|
539 |
+
"gpt_neox.layers.9.attention.query_key_value.bias": "pytorch_model-00001-of-00003.bin",
|
540 |
+
"gpt_neox.layers.9.attention.query_key_value.weight": "pytorch_model-00001-of-00003.bin",
|
541 |
+
"gpt_neox.layers.9.attention.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
542 |
+
"gpt_neox.layers.9.input_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
543 |
+
"gpt_neox.layers.9.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
544 |
+
"gpt_neox.layers.9.mlp.dense_4h_to_h.bias": "pytorch_model-00001-of-00003.bin",
|
545 |
+
"gpt_neox.layers.9.mlp.dense_4h_to_h.weight": "pytorch_model-00001-of-00003.bin",
|
546 |
+
"gpt_neox.layers.9.mlp.dense_h_to_4h.bias": "pytorch_model-00001-of-00003.bin",
|
547 |
+
"gpt_neox.layers.9.mlp.dense_h_to_4h.weight": "pytorch_model-00001-of-00003.bin",
|
548 |
+
"gpt_neox.layers.9.post_attention_layernorm.bias": "pytorch_model-00001-of-00003.bin",
|
549 |
+
"gpt_neox.layers.9.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin"
|
550 |
+
}
|
551 |
+
}
|
special_tokens_map.json
ADDED
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"additional_special_tokens": [
|
3 |
+
"</prefix>",
|
4 |
+
"<human>",
|
5 |
+
"<bot>",
|
6 |
+
"<prefix>"
|
7 |
+
],
|
8 |
+
"bos_token": "<|endoftext|>",
|
9 |
+
"eos_token": "<|endoftext|>",
|
10 |
+
"pad_token": "<|padding|>",
|
11 |
+
"sep_token": "<|endoftext|>",
|
12 |
+
"unk_token": "<|endoftext|>"
|
13 |
+
}
|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
tokenizer_config.json
ADDED
@@ -0,0 +1,10 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"add_prefix_space": false,
|
3 |
+
"bos_token": "<|endoftext|>",
|
4 |
+
"eos_token": "<|endoftext|>",
|
5 |
+
"model_max_length": 1000000000000000019884624838656,
|
6 |
+
"name_or_path": "EleutherAI/pythia-12b-deduped",
|
7 |
+
"special_tokens_map_file": "/fsx/home-hailey/.cache/huggingface/hub/models--EleutherAI--gpt-neox-20b/snapshots/3523781c8df75f7741687a4284f6f70e1afa12f4/special_tokens_map.json",
|
8 |
+
"tokenizer_class": "GPTNeoXTokenizer",
|
9 |
+
"unk_token": "<|endoftext|>"
|
10 |
+
}
|
trainer_state.json
ADDED
@@ -0,0 +1,1804 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"best_metric": null,
|
3 |
+
"best_model_checkpoint": null,
|
4 |
+
"epoch": 0.029488434635935788,
|
5 |
+
"global_step": 1000,
|
6 |
+
"is_hyper_param_search": false,
|
7 |
+
"is_local_process_zero": true,
|
8 |
+
"is_world_process_zero": true,
|
9 |
+
"log_history": [
|
10 |
+
{
|
11 |
+
"epoch": 0.0,
|
12 |
+
"learning_rate": 1.4084967333570947e-06,
|
13 |
+
"loss": 2.0409,
|
14 |
+
"step": 10
|
15 |
+
},
|
16 |
+
{
|
17 |
+
"epoch": 0.0,
|
18 |
+
"learning_rate": 2.0507482022971233e-06,
|
19 |
+
"loss": 1.8182,
|
20 |
+
"step": 20
|
21 |
+
},
|
22 |
+
{
|
23 |
+
"epoch": 0.0,
|
24 |
+
"learning_rate": 2.385606273598312e-06,
|
25 |
+
"loss": 1.6715,
|
26 |
+
"step": 30
|
27 |
+
},
|
28 |
+
{
|
29 |
+
"epoch": 0.0,
|
30 |
+
"learning_rate": 2.6136695401116585e-06,
|
31 |
+
"loss": 1.7864,
|
32 |
+
"step": 40
|
33 |
+
},
|
34 |
+
{
|
35 |
+
"epoch": 0.0,
|
36 |
+
"learning_rate": 2.7868297632261957e-06,
|
37 |
+
"loss": 1.6323,
|
38 |
+
"step": 50
|
39 |
+
},
|
40 |
+
{
|
41 |
+
"epoch": 0.0,
|
42 |
+
"learning_rate": 2.926458092787486e-06,
|
43 |
+
"loss": 1.6948,
|
44 |
+
"step": 60
|
45 |
+
},
|
46 |
+
{
|
47 |
+
"epoch": 0.0,
|
48 |
+
"learning_rate": 3.0434580045013773e-06,
|
49 |
+
"loss": 1.6492,
|
50 |
+
"step": 70
|
51 |
+
},
|
52 |
+
{
|
53 |
+
"epoch": 0.0,
|
54 |
+
"learning_rate": 3.1441512086208035e-06,
|
55 |
+
"loss": 1.6454,
|
56 |
+
"step": 80
|
57 |
+
},
|
58 |
+
{
|
59 |
+
"epoch": 0.0,
|
60 |
+
"learning_rate": 3.232532087697698e-06,
|
61 |
+
"loss": 1.6685,
|
62 |
+
"step": 90
|
63 |
+
},
|
64 |
+
{
|
65 |
+
"epoch": 0.0,
|
66 |
+
"learning_rate": 3.3112862237770753e-06,
|
67 |
+
"loss": 1.5988,
|
68 |
+
"step": 100
|
69 |
+
},
|
70 |
+
{
|
71 |
+
"epoch": 0.0,
|
72 |
+
"learning_rate": 3.3823062961420163e-06,
|
73 |
+
"loss": 1.5397,
|
74 |
+
"step": 110
|
75 |
+
},
|
76 |
+
{
|
77 |
+
"epoch": 0.0,
|
78 |
+
"learning_rate": 3.446976436243603e-06,
|
79 |
+
"loss": 1.6389,
|
80 |
+
"step": 120
|
81 |
+
},
|
82 |
+
{
|
83 |
+
"epoch": 0.0,
|
84 |
+
"learning_rate": 3.506339534926595e-06,
|
85 |
+
"loss": 1.5864,
|
86 |
+
"step": 130
|
87 |
+
},
|
88 |
+
{
|
89 |
+
"epoch": 0.0,
|
90 |
+
"learning_rate": 3.5612009452606784e-06,
|
91 |
+
"loss": 1.6896,
|
92 |
+
"step": 140
|
93 |
+
},
|
94 |
+
{
|
95 |
+
"epoch": 0.0,
|
96 |
+
"learning_rate": 3.612195557913627e-06,
|
97 |
+
"loss": 1.6217,
|
98 |
+
"step": 150
|
99 |
+
},
|
100 |
+
{
|
101 |
+
"epoch": 0.0,
|
102 |
+
"learning_rate": 3.65983275401539e-06,
|
103 |
+
"loss": 1.6265,
|
104 |
+
"step": 160
|
105 |
+
},
|
106 |
+
{
|
107 |
+
"epoch": 0.01,
|
108 |
+
"learning_rate": 3.7045274519126395e-06,
|
109 |
+
"loss": 1.6128,
|
110 |
+
"step": 170
|
111 |
+
},
|
112 |
+
{
|
113 |
+
"epoch": 0.01,
|
114 |
+
"learning_rate": 3.7466221106030114e-06,
|
115 |
+
"loss": 1.5282,
|
116 |
+
"step": 180
|
117 |
+
},
|
118 |
+
{
|
119 |
+
"epoch": 0.01,
|
120 |
+
"learning_rate": 3.786402677560832e-06,
|
121 |
+
"loss": 1.6623,
|
122 |
+
"step": 190
|
123 |
+
},
|
124 |
+
{
|
125 |
+
"epoch": 0.01,
|
126 |
+
"learning_rate": 3.824110376935989e-06,
|
127 |
+
"loss": 1.5958,
|
128 |
+
"step": 200
|
129 |
+
},
|
130 |
+
{
|
131 |
+
"epoch": 0.01,
|
132 |
+
"learning_rate": 3.8599505757615295e-06,
|
133 |
+
"loss": 1.6162,
|
134 |
+
"step": 210
|
135 |
+
},
|
136 |
+
{
|
137 |
+
"epoch": 0.01,
|
138 |
+
"learning_rate": 3.894099556414216e-06,
|
139 |
+
"loss": 1.5936,
|
140 |
+
"step": 220
|
141 |
+
},
|
142 |
+
{
|
143 |
+
"epoch": 0.01,
|
144 |
+
"learning_rate": 3.9267097619885385e-06,
|
145 |
+
"loss": 1.5658,
|
146 |
+
"step": 230
|
147 |
+
},
|
148 |
+
{
|
149 |
+
"epoch": 0.01,
|
150 |
+
"learning_rate": 3.95791391001684e-06,
|
151 |
+
"loss": 1.627,
|
152 |
+
"step": 240
|
153 |
+
},
|
154 |
+
{
|
155 |
+
"epoch": 0.01,
|
156 |
+
"learning_rate": 3.987828255432777e-06,
|
157 |
+
"loss": 1.6155,
|
158 |
+
"step": 250
|
159 |
+
},
|
160 |
+
{
|
161 |
+
"epoch": 0.01,
|
162 |
+
"eval_gsm8k_hard_accuracy": 0.8835755873132202,
|
163 |
+
"eval_gsm8k_hard_loss": 0.51513671875,
|
164 |
+
"eval_gsm8k_hard_runtime": 6.8667,
|
165 |
+
"eval_gsm8k_hard_samples_per_second": 38.446,
|
166 |
+
"eval_gsm8k_hard_steps_per_second": 0.437,
|
167 |
+
"step": 250
|
168 |
+
},
|
169 |
+
{
|
170 |
+
"epoch": 0.01,
|
171 |
+
"eval_webgpt_accuracy": 0.49985688262224126,
|
172 |
+
"eval_webgpt_loss": 2.197265625,
|
173 |
+
"eval_webgpt_runtime": 38.8229,
|
174 |
+
"eval_webgpt_samples_per_second": 100.868,
|
175 |
+
"eval_webgpt_steps_per_second": 1.056,
|
176 |
+
"step": 250
|
177 |
+
},
|
178 |
+
{
|
179 |
+
"epoch": 0.01,
|
180 |
+
"eval_squad_v2_accuracy": 0.8732225651432517,
|
181 |
+
"eval_squad_v2_loss": 0.394775390625,
|
182 |
+
"eval_squad_v2_runtime": 212.1787,
|
183 |
+
"eval_squad_v2_samples_per_second": 122.84,
|
184 |
+
"eval_squad_v2_steps_per_second": 1.282,
|
185 |
+
"step": 250
|
186 |
+
},
|
187 |
+
{
|
188 |
+
"epoch": 0.01,
|
189 |
+
"eval_adversarial_qa_accuracy": 0.7885436255634161,
|
190 |
+
"eval_adversarial_qa_loss": 0.84423828125,
|
191 |
+
"eval_adversarial_qa_runtime": 53.4145,
|
192 |
+
"eval_adversarial_qa_samples_per_second": 112.329,
|
193 |
+
"eval_adversarial_qa_steps_per_second": 1.179,
|
194 |
+
"step": 250
|
195 |
+
},
|
196 |
+
{
|
197 |
+
"epoch": 0.01,
|
198 |
+
"eval_private_tuning_accuracy": 0.6697048468296535,
|
199 |
+
"eval_private_tuning_loss": 1.234375,
|
200 |
+
"eval_private_tuning_runtime": 147.3821,
|
201 |
+
"eval_private_tuning_samples_per_second": 143.695,
|
202 |
+
"eval_private_tuning_steps_per_second": 1.5,
|
203 |
+
"step": 250
|
204 |
+
},
|
205 |
+
{
|
206 |
+
"epoch": 0.01,
|
207 |
+
"eval_oa_translated_accuracy": 0.6888436472902636,
|
208 |
+
"eval_oa_translated_loss": 1.271484375,
|
209 |
+
"eval_oa_translated_runtime": 1288.641,
|
210 |
+
"eval_oa_translated_samples_per_second": 91.051,
|
211 |
+
"eval_oa_translated_steps_per_second": 0.949,
|
212 |
+
"step": 250
|
213 |
+
},
|
214 |
+
{
|
215 |
+
"epoch": 0.01,
|
216 |
+
"eval_prosocial_dialogue_accuracy": 0.5277240036359349,
|
217 |
+
"eval_prosocial_dialogue_loss": 1.830078125,
|
218 |
+
"eval_prosocial_dialogue_runtime": 61.2751,
|
219 |
+
"eval_prosocial_dialogue_samples_per_second": 440.358,
|
220 |
+
"eval_prosocial_dialogue_steps_per_second": 4.602,
|
221 |
+
"step": 250
|
222 |
+
},
|
223 |
+
{
|
224 |
+
"epoch": 0.01,
|
225 |
+
"eval_math_qa_accuracy": 0.5650762200656649,
|
226 |
+
"eval_math_qa_loss": 1.912109375,
|
227 |
+
"eval_math_qa_runtime": 43.4013,
|
228 |
+
"eval_math_qa_samples_per_second": 137.507,
|
229 |
+
"eval_math_qa_steps_per_second": 1.452,
|
230 |
+
"step": 250
|
231 |
+
},
|
232 |
+
{
|
233 |
+
"epoch": 0.01,
|
234 |
+
"eval_wikihow_accuracy": 0.6096311191235613,
|
235 |
+
"eval_wikihow_loss": 1.8701171875,
|
236 |
+
"eval_wikihow_runtime": 16.5775,
|
237 |
+
"eval_wikihow_samples_per_second": 138.32,
|
238 |
+
"eval_wikihow_steps_per_second": 1.448,
|
239 |
+
"step": 250
|
240 |
+
},
|
241 |
+
{
|
242 |
+
"epoch": 0.01,
|
243 |
+
"eval_joke_accuracy": 0.49194465504169826,
|
244 |
+
"eval_joke_loss": 2.216796875,
|
245 |
+
"eval_joke_runtime": 2.4324,
|
246 |
+
"eval_joke_samples_per_second": 31.245,
|
247 |
+
"eval_joke_steps_per_second": 0.411,
|
248 |
+
"step": 250
|
249 |
+
},
|
250 |
+
{
|
251 |
+
"epoch": 0.01,
|
252 |
+
"eval_gsm8k_accuracy": 0.7494717398301172,
|
253 |
+
"eval_gsm8k_loss": 0.9765625,
|
254 |
+
"eval_gsm8k_runtime": 10.7538,
|
255 |
+
"eval_gsm8k_samples_per_second": 139.021,
|
256 |
+
"eval_gsm8k_steps_per_second": 1.488,
|
257 |
+
"step": 250
|
258 |
+
},
|
259 |
+
{
|
260 |
+
"epoch": 0.01,
|
261 |
+
"eval_ted_trans_en-hi_accuracy": 0.6902974158946855,
|
262 |
+
"eval_ted_trans_en-hi_loss": 1.1455078125,
|
263 |
+
"eval_ted_trans_en-hi_runtime": 4.0656,
|
264 |
+
"eval_ted_trans_en-hi_samples_per_second": 25.335,
|
265 |
+
"eval_ted_trans_en-hi_steps_per_second": 0.492,
|
266 |
+
"step": 250
|
267 |
+
},
|
268 |
+
{
|
269 |
+
"epoch": 0.01,
|
270 |
+
"eval_ted_trans_de-ja_accuracy": 0.6504194889162561,
|
271 |
+
"eval_ted_trans_de-ja_loss": 1.52734375,
|
272 |
+
"eval_ted_trans_de-ja_runtime": 8.8337,
|
273 |
+
"eval_ted_trans_de-ja_samples_per_second": 81.279,
|
274 |
+
"eval_ted_trans_de-ja_steps_per_second": 0.906,
|
275 |
+
"step": 250
|
276 |
+
},
|
277 |
+
{
|
278 |
+
"epoch": 0.01,
|
279 |
+
"eval_ted_trans_nl-en_accuracy": 0.7506186489759386,
|
280 |
+
"eval_ted_trans_nl-en_loss": 1.091796875,
|
281 |
+
"eval_ted_trans_nl-en_runtime": 8.871,
|
282 |
+
"eval_ted_trans_nl-en_samples_per_second": 86.913,
|
283 |
+
"eval_ted_trans_nl-en_steps_per_second": 1.015,
|
284 |
+
"step": 250
|
285 |
+
},
|
286 |
+
{
|
287 |
+
"epoch": 0.01,
|
288 |
+
"eval_ted_trans_en-ja_accuracy": 0.6557647009776333,
|
289 |
+
"eval_ted_trans_en-ja_loss": 1.427734375,
|
290 |
+
"eval_ted_trans_en-ja_runtime": 9.6821,
|
291 |
+
"eval_ted_trans_en-ja_samples_per_second": 82.73,
|
292 |
+
"eval_ted_trans_en-ja_steps_per_second": 0.93,
|
293 |
+
"step": 250
|
294 |
+
},
|
295 |
+
{
|
296 |
+
"epoch": 0.01,
|
297 |
+
"eval_ted_trans_en-es_accuracy": 0.7831022379328372,
|
298 |
+
"eval_ted_trans_en-es_loss": 0.89599609375,
|
299 |
+
"eval_ted_trans_en-es_runtime": 7.8367,
|
300 |
+
"eval_ted_trans_en-es_samples_per_second": 105.401,
|
301 |
+
"eval_ted_trans_en-es_steps_per_second": 1.148,
|
302 |
+
"step": 250
|
303 |
+
},
|
304 |
+
{
|
305 |
+
"epoch": 0.01,
|
306 |
+
"eval_ted_trans_en-ms_accuracy": 0.689470871191876,
|
307 |
+
"eval_ted_trans_en-ms_loss": 1.4052734375,
|
308 |
+
"eval_ted_trans_en-ms_runtime": 1.3714,
|
309 |
+
"eval_ted_trans_en-ms_samples_per_second": 30.625,
|
310 |
+
"eval_ted_trans_en-ms_steps_per_second": 0.729,
|
311 |
+
"step": 250
|
312 |
+
},
|
313 |
+
{
|
314 |
+
"epoch": 0.01,
|
315 |
+
"eval_xsum_accuracy": 0.6193833980292625,
|
316 |
+
"eval_xsum_loss": 1.4599609375,
|
317 |
+
"eval_xsum_runtime": 434.5368,
|
318 |
+
"eval_xsum_samples_per_second": 93.914,
|
319 |
+
"eval_xsum_steps_per_second": 0.98,
|
320 |
+
"step": 250
|
321 |
+
},
|
322 |
+
{
|
323 |
+
"epoch": 0.01,
|
324 |
+
"eval_cnn_dailymail_accuracy": 0.6712703040399833,
|
325 |
+
"eval_cnn_dailymail_loss": NaN,
|
326 |
+
"eval_cnn_dailymail_runtime": 624.2796,
|
327 |
+
"eval_cnn_dailymail_samples_per_second": 91.983,
|
328 |
+
"eval_cnn_dailymail_steps_per_second": 0.96,
|
329 |
+
"step": 250
|
330 |
+
},
|
331 |
+
{
|
332 |
+
"epoch": 0.01,
|
333 |
+
"eval_multi_news_accuracy": 0.5461545789406833,
|
334 |
+
"eval_multi_news_loss": NaN,
|
335 |
+
"eval_multi_news_runtime": 102.6315,
|
336 |
+
"eval_multi_news_samples_per_second": 87.644,
|
337 |
+
"eval_multi_news_steps_per_second": 0.916,
|
338 |
+
"step": 250
|
339 |
+
},
|
340 |
+
{
|
341 |
+
"epoch": 0.01,
|
342 |
+
"eval_tldr_news_accuracy": 0.5329163923633969,
|
343 |
+
"eval_tldr_news_loss": 2.1640625,
|
344 |
+
"eval_tldr_news_runtime": 7.304,
|
345 |
+
"eval_tldr_news_samples_per_second": 195.509,
|
346 |
+
"eval_tldr_news_steps_per_second": 2.054,
|
347 |
+
"step": 250
|
348 |
+
},
|
349 |
+
{
|
350 |
+
"epoch": 0.01,
|
351 |
+
"eval_scitldr_accuracy": 0.5056726094003241,
|
352 |
+
"eval_scitldr_loss": NaN,
|
353 |
+
"eval_scitldr_runtime": 6.0172,
|
354 |
+
"eval_scitldr_samples_per_second": 66.309,
|
355 |
+
"eval_scitldr_steps_per_second": 0.831,
|
356 |
+
"step": 250
|
357 |
+
},
|
358 |
+
{
|
359 |
+
"epoch": 0.01,
|
360 |
+
"eval_samsum_accuracy": 0.6255323175925049,
|
361 |
+
"eval_samsum_loss": 1.390625,
|
362 |
+
"eval_samsum_runtime": 31.2731,
|
363 |
+
"eval_samsum_samples_per_second": 94.234,
|
364 |
+
"eval_samsum_steps_per_second": 0.991,
|
365 |
+
"step": 250
|
366 |
+
},
|
367 |
+
{
|
368 |
+
"epoch": 0.01,
|
369 |
+
"eval_debate_sum_accuracy": 0.934249098160658,
|
370 |
+
"eval_debate_sum_loss": 0.363525390625,
|
371 |
+
"eval_debate_sum_runtime": 539.9242,
|
372 |
+
"eval_debate_sum_samples_per_second": 89.113,
|
373 |
+
"eval_debate_sum_steps_per_second": 0.93,
|
374 |
+
"step": 250
|
375 |
+
},
|
376 |
+
{
|
377 |
+
"epoch": 0.01,
|
378 |
+
"eval_billsum_accuracy": 0.6761362636279469,
|
379 |
+
"eval_billsum_loss": 1.3681640625,
|
380 |
+
"eval_billsum_runtime": 47.9835,
|
381 |
+
"eval_billsum_samples_per_second": 78.985,
|
382 |
+
"eval_billsum_steps_per_second": 0.834,
|
383 |
+
"step": 250
|
384 |
+
},
|
385 |
+
{
|
386 |
+
"epoch": 0.01,
|
387 |
+
"eval_wmt2019_zh-en_accuracy": 0.6633805205208717,
|
388 |
+
"eval_wmt2019_zh-en_loss": 1.474609375,
|
389 |
+
"eval_wmt2019_zh-en_runtime": 27.1758,
|
390 |
+
"eval_wmt2019_zh-en_samples_per_second": 146.491,
|
391 |
+
"eval_wmt2019_zh-en_steps_per_second": 1.545,
|
392 |
+
"step": 250
|
393 |
+
},
|
394 |
+
{
|
395 |
+
"epoch": 0.01,
|
396 |
+
"eval_wmt2019_ru-en_accuracy": 0.7568385011868931,
|
397 |
+
"eval_wmt2019_ru-en_loss": 0.9365234375,
|
398 |
+
"eval_wmt2019_ru-en_runtime": 21.7646,
|
399 |
+
"eval_wmt2019_ru-en_samples_per_second": 137.839,
|
400 |
+
"eval_wmt2019_ru-en_steps_per_second": 1.47,
|
401 |
+
"step": 250
|
402 |
+
},
|
403 |
+
{
|
404 |
+
"epoch": 0.01,
|
405 |
+
"eval_wmt2019_de-en_accuracy": 0.7579152898768399,
|
406 |
+
"eval_wmt2019_de-en_loss": 0.94921875,
|
407 |
+
"eval_wmt2019_de-en_runtime": 15.095,
|
408 |
+
"eval_wmt2019_de-en_samples_per_second": 198.609,
|
409 |
+
"eval_wmt2019_de-en_steps_per_second": 2.12,
|
410 |
+
"step": 250
|
411 |
+
},
|
412 |
+
{
|
413 |
+
"epoch": 0.01,
|
414 |
+
"eval_wmt2019_fr-de_accuracy": 0.7458755561047948,
|
415 |
+
"eval_wmt2019_fr-de_loss": 1.0107421875,
|
416 |
+
"eval_wmt2019_fr-de_runtime": 10.8089,
|
417 |
+
"eval_wmt2019_fr-de_samples_per_second": 139.885,
|
418 |
+
"eval_wmt2019_fr-de_steps_per_second": 1.48,
|
419 |
+
"step": 250
|
420 |
+
},
|
421 |
+
{
|
422 |
+
"epoch": 0.01,
|
423 |
+
"eval_essay_instruction_accuracy": 0.5980087566061517,
|
424 |
+
"eval_essay_instruction_loss": 1.939453125,
|
425 |
+
"eval_essay_instruction_runtime": 8.5102,
|
426 |
+
"eval_essay_instruction_samples_per_second": 48.53,
|
427 |
+
"eval_essay_instruction_steps_per_second": 0.588,
|
428 |
+
"step": 250
|
429 |
+
},
|
430 |
+
{
|
431 |
+
"epoch": 0.01,
|
432 |
+
"eval_reddit_eli5_accuracy": 0.4587571011238715,
|
433 |
+
"eval_reddit_eli5_loss": 2.43359375,
|
434 |
+
"eval_reddit_eli5_runtime": 592.806,
|
435 |
+
"eval_reddit_eli5_samples_per_second": 91.981,
|
436 |
+
"eval_reddit_eli5_steps_per_second": 0.958,
|
437 |
+
"step": 250
|
438 |
+
},
|
439 |
+
{
|
440 |
+
"epoch": 0.01,
|
441 |
+
"eval_reddit_askh_accuracy": 0.46236593037589085,
|
442 |
+
"eval_reddit_askh_loss": 2.53125,
|
443 |
+
"eval_reddit_askh_runtime": 245.8916,
|
444 |
+
"eval_reddit_askh_samples_per_second": 80.137,
|
445 |
+
"eval_reddit_askh_steps_per_second": 0.838,
|
446 |
+
"step": 250
|
447 |
+
},
|
448 |
+
{
|
449 |
+
"epoch": 0.01,
|
450 |
+
"eval_reddit_asks_accuracy": 0.4693832359074744,
|
451 |
+
"eval_reddit_asks_loss": 2.390625,
|
452 |
+
"eval_reddit_asks_runtime": 307.0019,
|
453 |
+
"eval_reddit_asks_samples_per_second": 85.85,
|
454 |
+
"eval_reddit_asks_steps_per_second": 0.896,
|
455 |
+
"step": 250
|
456 |
+
},
|
457 |
+
{
|
458 |
+
"epoch": 0.01,
|
459 |
+
"learning_rate": 4.016555205552159e-06,
|
460 |
+
"loss": 1.6024,
|
461 |
+
"step": 260
|
462 |
+
},
|
463 |
+
{
|
464 |
+
"epoch": 0.01,
|
465 |
+
"learning_rate": 4.044185435607626e-06,
|
466 |
+
"loss": 1.6344,
|
467 |
+
"step": 270
|
468 |
+
},
|
469 |
+
{
|
470 |
+
"epoch": 0.01,
|
471 |
+
"learning_rate": 4.070799615107415e-06,
|
472 |
+
"loss": 1.5251,
|
473 |
+
"step": 280
|
474 |
+
},
|
475 |
+
{
|
476 |
+
"epoch": 0.01,
|
477 |
+
"learning_rate": 4.096469827889988e-06,
|
478 |
+
"loss": 1.5818,
|
479 |
+
"step": 290
|
480 |
+
},
|
481 |
+
{
|
482 |
+
"epoch": 0.01,
|
483 |
+
"learning_rate": 4.121260748862021e-06,
|
484 |
+
"loss": 1.6331,
|
485 |
+
"step": 300
|
486 |
+
},
|
487 |
+
{
|
488 |
+
"epoch": 0.01,
|
489 |
+
"learning_rate": 4.145230625795312e-06,
|
490 |
+
"loss": 1.6272,
|
491 |
+
"step": 310
|
492 |
+
},
|
493 |
+
{
|
494 |
+
"epoch": 0.01,
|
495 |
+
"learning_rate": 4.1684321036962525e-06,
|
496 |
+
"loss": 1.5872,
|
497 |
+
"step": 320
|
498 |
+
},
|
499 |
+
{
|
500 |
+
"epoch": 0.01,
|
501 |
+
"learning_rate": 4.190912921100477e-06,
|
502 |
+
"loss": 1.6504,
|
503 |
+
"step": 330
|
504 |
+
},
|
505 |
+
{
|
506 |
+
"epoch": 0.01,
|
507 |
+
"learning_rate": 4.212716501452232e-06,
|
508 |
+
"loss": 1.566,
|
509 |
+
"step": 340
|
510 |
+
},
|
511 |
+
{
|
512 |
+
"epoch": 0.01,
|
513 |
+
"learning_rate": 4.233882457984791e-06,
|
514 |
+
"loss": 1.6106,
|
515 |
+
"step": 350
|
516 |
+
},
|
517 |
+
{
|
518 |
+
"epoch": 0.01,
|
519 |
+
"learning_rate": 4.2544470268536555e-06,
|
520 |
+
"loss": 1.616,
|
521 |
+
"step": 360
|
522 |
+
},
|
523 |
+
{
|
524 |
+
"epoch": 0.01,
|
525 |
+
"learning_rate": 4.27444344042015e-06,
|
526 |
+
"loss": 1.6374,
|
527 |
+
"step": 370
|
528 |
+
},
|
529 |
+
{
|
530 |
+
"epoch": 0.01,
|
531 |
+
"learning_rate": 4.293902250342989e-06,
|
532 |
+
"loss": 1.5941,
|
533 |
+
"step": 380
|
534 |
+
},
|
535 |
+
{
|
536 |
+
"epoch": 0.01,
|
537 |
+
"learning_rate": 4.312851608364853e-06,
|
538 |
+
"loss": 1.6115,
|
539 |
+
"step": 390
|
540 |
+
},
|
541 |
+
{
|
542 |
+
"epoch": 0.01,
|
543 |
+
"learning_rate": 4.3313175112718595e-06,
|
544 |
+
"loss": 1.5531,
|
545 |
+
"step": 400
|
546 |
+
},
|
547 |
+
{
|
548 |
+
"epoch": 0.01,
|
549 |
+
"learning_rate": 4.3493240153753665e-06,
|
550 |
+
"loss": 1.5554,
|
551 |
+
"step": 410
|
552 |
+
},
|
553 |
+
{
|
554 |
+
"epoch": 0.01,
|
555 |
+
"learning_rate": 4.366893424956263e-06,
|
556 |
+
"loss": 1.5233,
|
557 |
+
"step": 420
|
558 |
+
},
|
559 |
+
{
|
560 |
+
"epoch": 0.01,
|
561 |
+
"learning_rate": 4.38404645837504e-06,
|
562 |
+
"loss": 1.5579,
|
563 |
+
"step": 430
|
564 |
+
},
|
565 |
+
{
|
566 |
+
"epoch": 0.01,
|
567 |
+
"learning_rate": 4.400802394950703e-06,
|
568 |
+
"loss": 1.6028,
|
569 |
+
"step": 440
|
570 |
+
},
|
571 |
+
{
|
572 |
+
"epoch": 0.01,
|
573 |
+
"learning_rate": 4.4171792052198945e-06,
|
574 |
+
"loss": 1.5239,
|
575 |
+
"step": 450
|
576 |
+
},
|
577 |
+
{
|
578 |
+
"epoch": 0.01,
|
579 |
+
"learning_rate": 4.433193666783084e-06,
|
580 |
+
"loss": 1.6149,
|
581 |
+
"step": 460
|
582 |
+
},
|
583 |
+
{
|
584 |
+
"epoch": 0.01,
|
585 |
+
"learning_rate": 4.448861467610187e-06,
|
586 |
+
"loss": 1.6114,
|
587 |
+
"step": 470
|
588 |
+
},
|
589 |
+
{
|
590 |
+
"epoch": 0.01,
|
591 |
+
"learning_rate": 4.4641972984001906e-06,
|
592 |
+
"loss": 1.6682,
|
593 |
+
"step": 480
|
594 |
+
},
|
595 |
+
{
|
596 |
+
"epoch": 0.01,
|
597 |
+
"learning_rate": 4.479214935357724e-06,
|
598 |
+
"loss": 1.5707,
|
599 |
+
"step": 490
|
600 |
+
},
|
601 |
+
{
|
602 |
+
"epoch": 0.01,
|
603 |
+
"learning_rate": 4.493927314555554e-06,
|
604 |
+
"loss": 1.5827,
|
605 |
+
"step": 500
|
606 |
+
},
|
607 |
+
{
|
608 |
+
"epoch": 0.01,
|
609 |
+
"eval_gsm8k_hard_accuracy": 0.9183054435894304,
|
610 |
+
"eval_gsm8k_hard_loss": 0.3740234375,
|
611 |
+
"eval_gsm8k_hard_runtime": 3.8504,
|
612 |
+
"eval_gsm8k_hard_samples_per_second": 68.565,
|
613 |
+
"eval_gsm8k_hard_steps_per_second": 0.779,
|
614 |
+
"step": 500
|
615 |
+
},
|
616 |
+
{
|
617 |
+
"epoch": 0.01,
|
618 |
+
"eval_webgpt_accuracy": 0.502614994399395,
|
619 |
+
"eval_webgpt_loss": 2.185546875,
|
620 |
+
"eval_webgpt_runtime": 37.4417,
|
621 |
+
"eval_webgpt_samples_per_second": 104.589,
|
622 |
+
"eval_webgpt_steps_per_second": 1.095,
|
623 |
+
"step": 500
|
624 |
+
},
|
625 |
+
{
|
626 |
+
"epoch": 0.01,
|
627 |
+
"eval_squad_v2_accuracy": 0.8982722417170479,
|
628 |
+
"eval_squad_v2_loss": 0.33447265625,
|
629 |
+
"eval_squad_v2_runtime": 214.9352,
|
630 |
+
"eval_squad_v2_samples_per_second": 121.264,
|
631 |
+
"eval_squad_v2_steps_per_second": 1.265,
|
632 |
+
"step": 500
|
633 |
+
},
|
634 |
+
{
|
635 |
+
"epoch": 0.01,
|
636 |
+
"eval_adversarial_qa_accuracy": 0.8046625473866452,
|
637 |
+
"eval_adversarial_qa_loss": 0.8486328125,
|
638 |
+
"eval_adversarial_qa_runtime": 51.9881,
|
639 |
+
"eval_adversarial_qa_samples_per_second": 115.411,
|
640 |
+
"eval_adversarial_qa_steps_per_second": 1.212,
|
641 |
+
"step": 500
|
642 |
+
},
|
643 |
+
{
|
644 |
+
"epoch": 0.01,
|
645 |
+
"eval_private_tuning_accuracy": 0.6754279825666092,
|
646 |
+
"eval_private_tuning_loss": 1.20703125,
|
647 |
+
"eval_private_tuning_runtime": 143.688,
|
648 |
+
"eval_private_tuning_samples_per_second": 147.389,
|
649 |
+
"eval_private_tuning_steps_per_second": 1.538,
|
650 |
+
"step": 500
|
651 |
+
},
|
652 |
+
{
|
653 |
+
"epoch": 0.01,
|
654 |
+
"eval_oa_translated_accuracy": 0.6956755454438557,
|
655 |
+
"eval_oa_translated_loss": 1.2421875,
|
656 |
+
"eval_oa_translated_runtime": 1298.0566,
|
657 |
+
"eval_oa_translated_samples_per_second": 90.391,
|
658 |
+
"eval_oa_translated_steps_per_second": 0.942,
|
659 |
+
"step": 500
|
660 |
+
},
|
661 |
+
{
|
662 |
+
"epoch": 0.01,
|
663 |
+
"eval_prosocial_dialogue_accuracy": 0.5306487253309804,
|
664 |
+
"eval_prosocial_dialogue_loss": 1.783203125,
|
665 |
+
"eval_prosocial_dialogue_runtime": 62.6995,
|
666 |
+
"eval_prosocial_dialogue_samples_per_second": 430.355,
|
667 |
+
"eval_prosocial_dialogue_steps_per_second": 4.498,
|
668 |
+
"step": 500
|
669 |
+
},
|
670 |
+
{
|
671 |
+
"epoch": 0.01,
|
672 |
+
"eval_math_qa_accuracy": 0.573035368807606,
|
673 |
+
"eval_math_qa_loss": 1.849609375,
|
674 |
+
"eval_math_qa_runtime": 42.0578,
|
675 |
+
"eval_math_qa_samples_per_second": 141.9,
|
676 |
+
"eval_math_qa_steps_per_second": 1.498,
|
677 |
+
"step": 500
|
678 |
+
},
|
679 |
+
{
|
680 |
+
"epoch": 0.01,
|
681 |
+
"eval_wikihow_accuracy": 0.6166412425461101,
|
682 |
+
"eval_wikihow_loss": 1.8369140625,
|
683 |
+
"eval_wikihow_runtime": 17.5874,
|
684 |
+
"eval_wikihow_samples_per_second": 130.377,
|
685 |
+
"eval_wikihow_steps_per_second": 1.365,
|
686 |
+
"step": 500
|
687 |
+
},
|
688 |
+
{
|
689 |
+
"epoch": 0.01,
|
690 |
+
"eval_joke_accuracy": 0.500284306292646,
|
691 |
+
"eval_joke_loss": 2.1875,
|
692 |
+
"eval_joke_runtime": 1.5291,
|
693 |
+
"eval_joke_samples_per_second": 49.704,
|
694 |
+
"eval_joke_steps_per_second": 0.654,
|
695 |
+
"step": 500
|
696 |
+
},
|
697 |
+
{
|
698 |
+
"epoch": 0.01,
|
699 |
+
"eval_gsm8k_accuracy": 0.7605687018093785,
|
700 |
+
"eval_gsm8k_loss": 0.91357421875,
|
701 |
+
"eval_gsm8k_runtime": 11.3759,
|
702 |
+
"eval_gsm8k_samples_per_second": 131.418,
|
703 |
+
"eval_gsm8k_steps_per_second": 1.406,
|
704 |
+
"step": 500
|
705 |
+
},
|
706 |
+
{
|
707 |
+
"epoch": 0.01,
|
708 |
+
"eval_ted_trans_en-hi_accuracy": 0.6839278864595321,
|
709 |
+
"eval_ted_trans_en-hi_loss": 1.142578125,
|
710 |
+
"eval_ted_trans_en-hi_runtime": 2.7736,
|
711 |
+
"eval_ted_trans_en-hi_samples_per_second": 37.135,
|
712 |
+
"eval_ted_trans_en-hi_steps_per_second": 0.721,
|
713 |
+
"step": 500
|
714 |
+
},
|
715 |
+
{
|
716 |
+
"epoch": 0.01,
|
717 |
+
"eval_ted_trans_de-ja_accuracy": 0.6501228312605558,
|
718 |
+
"eval_ted_trans_de-ja_loss": 1.5048828125,
|
719 |
+
"eval_ted_trans_de-ja_runtime": 8.2515,
|
720 |
+
"eval_ted_trans_de-ja_samples_per_second": 87.014,
|
721 |
+
"eval_ted_trans_de-ja_steps_per_second": 0.97,
|
722 |
+
"step": 500
|
723 |
+
},
|
724 |
+
{
|
725 |
+
"epoch": 0.01,
|
726 |
+
"eval_ted_trans_nl-en_accuracy": 0.7532021898001414,
|
727 |
+
"eval_ted_trans_nl-en_loss": 1.0654296875,
|
728 |
+
"eval_ted_trans_nl-en_runtime": 7.9186,
|
729 |
+
"eval_ted_trans_nl-en_samples_per_second": 97.365,
|
730 |
+
"eval_ted_trans_nl-en_steps_per_second": 1.137,
|
731 |
+
"step": 500
|
732 |
+
},
|
733 |
+
{
|
734 |
+
"epoch": 0.01,
|
735 |
+
"eval_ted_trans_en-ja_accuracy": 0.6662950575994054,
|
736 |
+
"eval_ted_trans_en-ja_loss": 1.3916015625,
|
737 |
+
"eval_ted_trans_en-ja_runtime": 9.7107,
|
738 |
+
"eval_ted_trans_en-ja_samples_per_second": 82.486,
|
739 |
+
"eval_ted_trans_en-ja_steps_per_second": 0.927,
|
740 |
+
"step": 500
|
741 |
+
},
|
742 |
+
{
|
743 |
+
"epoch": 0.01,
|
744 |
+
"eval_ted_trans_en-es_accuracy": 0.7895431674388482,
|
745 |
+
"eval_ted_trans_en-es_loss": 0.87646484375,
|
746 |
+
"eval_ted_trans_en-es_runtime": 9.3046,
|
747 |
+
"eval_ted_trans_en-es_samples_per_second": 88.774,
|
748 |
+
"eval_ted_trans_en-es_steps_per_second": 0.967,
|
749 |
+
"step": 500
|
750 |
+
},
|
751 |
+
{
|
752 |
+
"epoch": 0.01,
|
753 |
+
"eval_ted_trans_en-ms_accuracy": 0.692143238909674,
|
754 |
+
"eval_ted_trans_en-ms_loss": 1.36328125,
|
755 |
+
"eval_ted_trans_en-ms_runtime": 1.0241,
|
756 |
+
"eval_ted_trans_en-ms_samples_per_second": 41.011,
|
757 |
+
"eval_ted_trans_en-ms_steps_per_second": 0.976,
|
758 |
+
"step": 500
|
759 |
+
},
|
760 |
+
{
|
761 |
+
"epoch": 0.01,
|
762 |
+
"eval_xsum_accuracy": 0.621155930594,
|
763 |
+
"eval_xsum_loss": 1.4501953125,
|
764 |
+
"eval_xsum_runtime": 440.7691,
|
765 |
+
"eval_xsum_samples_per_second": 92.586,
|
766 |
+
"eval_xsum_steps_per_second": 0.966,
|
767 |
+
"step": 500
|
768 |
+
},
|
769 |
+
{
|
770 |
+
"epoch": 0.01,
|
771 |
+
"eval_cnn_dailymail_accuracy": 0.6818918043407839,
|
772 |
+
"eval_cnn_dailymail_loss": NaN,
|
773 |
+
"eval_cnn_dailymail_runtime": 631.5892,
|
774 |
+
"eval_cnn_dailymail_samples_per_second": 90.918,
|
775 |
+
"eval_cnn_dailymail_steps_per_second": 0.948,
|
776 |
+
"step": 500
|
777 |
+
},
|
778 |
+
{
|
779 |
+
"epoch": 0.01,
|
780 |
+
"eval_multi_news_accuracy": 0.5512987425377873,
|
781 |
+
"eval_multi_news_loss": NaN,
|
782 |
+
"eval_multi_news_runtime": 102.5343,
|
783 |
+
"eval_multi_news_samples_per_second": 87.727,
|
784 |
+
"eval_multi_news_steps_per_second": 0.917,
|
785 |
+
"step": 500
|
786 |
+
},
|
787 |
+
{
|
788 |
+
"epoch": 0.01,
|
789 |
+
"eval_tldr_news_accuracy": 0.5479638860152356,
|
790 |
+
"eval_tldr_news_loss": 2.09375,
|
791 |
+
"eval_tldr_news_runtime": 7.6366,
|
792 |
+
"eval_tldr_news_samples_per_second": 186.994,
|
793 |
+
"eval_tldr_news_steps_per_second": 1.964,
|
794 |
+
"step": 500
|
795 |
+
},
|
796 |
+
{
|
797 |
+
"epoch": 0.01,
|
798 |
+
"eval_scitldr_accuracy": 0.4991896272285251,
|
799 |
+
"eval_scitldr_loss": NaN,
|
800 |
+
"eval_scitldr_runtime": 5.9643,
|
801 |
+
"eval_scitldr_samples_per_second": 66.899,
|
802 |
+
"eval_scitldr_steps_per_second": 0.838,
|
803 |
+
"step": 500
|
804 |
+
},
|
805 |
+
{
|
806 |
+
"epoch": 0.01,
|
807 |
+
"eval_samsum_accuracy": 0.6392542821992997,
|
808 |
+
"eval_samsum_loss": 1.3603515625,
|
809 |
+
"eval_samsum_runtime": 31.1036,
|
810 |
+
"eval_samsum_samples_per_second": 94.748,
|
811 |
+
"eval_samsum_steps_per_second": 0.997,
|
812 |
+
"step": 500
|
813 |
+
},
|
814 |
+
{
|
815 |
+
"epoch": 0.01,
|
816 |
+
"eval_debate_sum_accuracy": 0.9375640253883767,
|
817 |
+
"eval_debate_sum_loss": 0.34521484375,
|
818 |
+
"eval_debate_sum_runtime": 548.5555,
|
819 |
+
"eval_debate_sum_samples_per_second": 87.71,
|
820 |
+
"eval_debate_sum_steps_per_second": 0.915,
|
821 |
+
"step": 500
|
822 |
+
},
|
823 |
+
{
|
824 |
+
"epoch": 0.01,
|
825 |
+
"eval_billsum_accuracy": 0.6806867345609693,
|
826 |
+
"eval_billsum_loss": 1.3427734375,
|
827 |
+
"eval_billsum_runtime": 43.496,
|
828 |
+
"eval_billsum_samples_per_second": 87.134,
|
829 |
+
"eval_billsum_steps_per_second": 0.92,
|
830 |
+
"step": 500
|
831 |
+
},
|
832 |
+
{
|
833 |
+
"epoch": 0.01,
|
834 |
+
"eval_wmt2019_zh-en_accuracy": 0.6670238429829493,
|
835 |
+
"eval_wmt2019_zh-en_loss": 1.453125,
|
836 |
+
"eval_wmt2019_zh-en_runtime": 28.9371,
|
837 |
+
"eval_wmt2019_zh-en_samples_per_second": 137.574,
|
838 |
+
"eval_wmt2019_zh-en_steps_per_second": 1.451,
|
839 |
+
"step": 500
|
840 |
+
},
|
841 |
+
{
|
842 |
+
"epoch": 0.01,
|
843 |
+
"eval_wmt2019_ru-en_accuracy": 0.7587101830765136,
|
844 |
+
"eval_wmt2019_ru-en_loss": 0.92724609375,
|
845 |
+
"eval_wmt2019_ru-en_runtime": 23.7381,
|
846 |
+
"eval_wmt2019_ru-en_samples_per_second": 126.379,
|
847 |
+
"eval_wmt2019_ru-en_steps_per_second": 1.348,
|
848 |
+
"step": 500
|
849 |
+
},
|
850 |
+
{
|
851 |
+
"epoch": 0.01,
|
852 |
+
"eval_wmt2019_de-en_accuracy": 0.7675478121558026,
|
853 |
+
"eval_wmt2019_de-en_loss": 0.90478515625,
|
854 |
+
"eval_wmt2019_de-en_runtime": 16.2264,
|
855 |
+
"eval_wmt2019_de-en_samples_per_second": 184.76,
|
856 |
+
"eval_wmt2019_de-en_steps_per_second": 1.972,
|
857 |
+
"step": 500
|
858 |
+
},
|
859 |
+
{
|
860 |
+
"epoch": 0.01,
|
861 |
+
"eval_wmt2019_fr-de_accuracy": 0.7500888456249324,
|
862 |
+
"eval_wmt2019_fr-de_loss": 0.99560546875,
|
863 |
+
"eval_wmt2019_fr-de_runtime": 11.5712,
|
864 |
+
"eval_wmt2019_fr-de_samples_per_second": 130.669,
|
865 |
+
"eval_wmt2019_fr-de_steps_per_second": 1.383,
|
866 |
+
"step": 500
|
867 |
+
},
|
868 |
+
{
|
869 |
+
"epoch": 0.01,
|
870 |
+
"eval_essay_instruction_accuracy": 0.6002366052672313,
|
871 |
+
"eval_essay_instruction_loss": 1.9189453125,
|
872 |
+
"eval_essay_instruction_runtime": 8.0794,
|
873 |
+
"eval_essay_instruction_samples_per_second": 51.118,
|
874 |
+
"eval_essay_instruction_steps_per_second": 0.619,
|
875 |
+
"step": 500
|
876 |
+
},
|
877 |
+
{
|
878 |
+
"epoch": 0.01,
|
879 |
+
"eval_reddit_eli5_accuracy": 0.46082089893518746,
|
880 |
+
"eval_reddit_eli5_loss": 2.4296875,
|
881 |
+
"eval_reddit_eli5_runtime": 602.6271,
|
882 |
+
"eval_reddit_eli5_samples_per_second": 90.482,
|
883 |
+
"eval_reddit_eli5_steps_per_second": 0.943,
|
884 |
+
"step": 500
|
885 |
+
},
|
886 |
+
{
|
887 |
+
"epoch": 0.01,
|
888 |
+
"eval_reddit_askh_accuracy": 0.46347532552175574,
|
889 |
+
"eval_reddit_askh_loss": 2.52734375,
|
890 |
+
"eval_reddit_askh_runtime": 245.7671,
|
891 |
+
"eval_reddit_askh_samples_per_second": 80.178,
|
892 |
+
"eval_reddit_askh_steps_per_second": 0.838,
|
893 |
+
"step": 500
|
894 |
+
},
|
895 |
+
{
|
896 |
+
"epoch": 0.01,
|
897 |
+
"eval_reddit_asks_accuracy": 0.47150193020881753,
|
898 |
+
"eval_reddit_asks_loss": 2.38671875,
|
899 |
+
"eval_reddit_asks_runtime": 320.7509,
|
900 |
+
"eval_reddit_asks_samples_per_second": 82.17,
|
901 |
+
"eval_reddit_asks_steps_per_second": 0.857,
|
902 |
+
"step": 500
|
903 |
+
},
|
904 |
+
{
|
905 |
+
"epoch": 0.02,
|
906 |
+
"learning_rate": 4.5083465988888945e-06,
|
907 |
+
"loss": 1.5195,
|
908 |
+
"step": 510
|
909 |
+
},
|
910 |
+
{
|
911 |
+
"epoch": 0.02,
|
912 |
+
"learning_rate": 4.5224842384899045e-06,
|
913 |
+
"loss": 1.492,
|
914 |
+
"step": 520
|
915 |
+
},
|
916 |
+
{
|
917 |
+
"epoch": 0.02,
|
918 |
+
"learning_rate": 4.5363510253542444e-06,
|
919 |
+
"loss": 1.5302,
|
920 |
+
"step": 530
|
921 |
+
},
|
922 |
+
{
|
923 |
+
"epoch": 0.02,
|
924 |
+
"learning_rate": 4.549957142832593e-06,
|
925 |
+
"loss": 1.5267,
|
926 |
+
"step": 540
|
927 |
+
},
|
928 |
+
{
|
929 |
+
"epoch": 0.02,
|
930 |
+
"learning_rate": 4.563312210555719e-06,
|
931 |
+
"loss": 1.565,
|
932 |
+
"step": 550
|
933 |
+
},
|
934 |
+
{
|
935 |
+
"epoch": 0.02,
|
936 |
+
"learning_rate": 4.576425325289549e-06,
|
937 |
+
"loss": 1.6208,
|
938 |
+
"step": 560
|
939 |
+
},
|
940 |
+
{
|
941 |
+
"epoch": 0.02,
|
942 |
+
"learning_rate": 4.589305098154845e-06,
|
943 |
+
"loss": 1.6341,
|
944 |
+
"step": 570
|
945 |
+
},
|
946 |
+
{
|
947 |
+
"epoch": 0.02,
|
948 |
+
"learning_rate": 4.601959688592886e-06,
|
949 |
+
"loss": 1.5639,
|
950 |
+
"step": 580
|
951 |
+
},
|
952 |
+
{
|
953 |
+
"epoch": 0.02,
|
954 |
+
"learning_rate": 4.614396835412691e-06,
|
955 |
+
"loss": 1.6218,
|
956 |
+
"step": 590
|
957 |
+
},
|
958 |
+
{
|
959 |
+
"epoch": 0.02,
|
960 |
+
"learning_rate": 4.626623885215616e-06,
|
961 |
+
"loss": 1.5995,
|
962 |
+
"step": 600
|
963 |
+
},
|
964 |
+
{
|
965 |
+
"epoch": 0.02,
|
966 |
+
"learning_rate": 4.638647818458763e-06,
|
967 |
+
"loss": 1.6176,
|
968 |
+
"step": 610
|
969 |
+
},
|
970 |
+
{
|
971 |
+
"epoch": 0.02,
|
972 |
+
"learning_rate": 4.650475273388737e-06,
|
973 |
+
"loss": 1.5944,
|
974 |
+
"step": 620
|
975 |
+
},
|
976 |
+
{
|
977 |
+
"epoch": 0.02,
|
978 |
+
"learning_rate": 4.662112568051194e-06,
|
979 |
+
"loss": 1.6074,
|
980 |
+
"step": 630
|
981 |
+
},
|
982 |
+
{
|
983 |
+
"epoch": 0.02,
|
984 |
+
"learning_rate": 4.673565720558918e-06,
|
985 |
+
"loss": 1.5783,
|
986 |
+
"step": 640
|
987 |
+
},
|
988 |
+
{
|
989 |
+
"epoch": 0.02,
|
990 |
+
"learning_rate": 4.6848404677811685e-06,
|
991 |
+
"loss": 1.5135,
|
992 |
+
"step": 650
|
993 |
+
},
|
994 |
+
{
|
995 |
+
"epoch": 0.02,
|
996 |
+
"learning_rate": 4.695942282599635e-06,
|
997 |
+
"loss": 1.6396,
|
998 |
+
"step": 660
|
999 |
+
},
|
1000 |
+
{
|
1001 |
+
"epoch": 0.02,
|
1002 |
+
"learning_rate": 4.706876389860915e-06,
|
1003 |
+
"loss": 1.6053,
|
1004 |
+
"step": 670
|
1005 |
+
},
|
1006 |
+
{
|
1007 |
+
"epoch": 0.02,
|
1008 |
+
"learning_rate": 4.717647781141908e-06,
|
1009 |
+
"loss": 1.5982,
|
1010 |
+
"step": 680
|
1011 |
+
},
|
1012 |
+
{
|
1013 |
+
"epoch": 0.02,
|
1014 |
+
"learning_rate": 4.7282612284325845e-06,
|
1015 |
+
"loss": 1.5361,
|
1016 |
+
"step": 690
|
1017 |
+
},
|
1018 |
+
{
|
1019 |
+
"epoch": 0.02,
|
1020 |
+
"learning_rate": 4.738721296830016e-06,
|
1021 |
+
"loss": 1.5127,
|
1022 |
+
"step": 700
|
1023 |
+
},
|
1024 |
+
{
|
1025 |
+
"epoch": 0.02,
|
1026 |
+
"learning_rate": 4.749032356328167e-06,
|
1027 |
+
"loss": 1.4852,
|
1028 |
+
"step": 710
|
1029 |
+
},
|
1030 |
+
{
|
1031 |
+
"epoch": 0.02,
|
1032 |
+
"learning_rate": 4.759198592779668e-06,
|
1033 |
+
"loss": 1.5432,
|
1034 |
+
"step": 720
|
1035 |
+
},
|
1036 |
+
{
|
1037 |
+
"epoch": 0.02,
|
1038 |
+
"learning_rate": 4.769224018098397e-06,
|
1039 |
+
"loss": 1.5425,
|
1040 |
+
"step": 730
|
1041 |
+
},
|
1042 |
+
{
|
1043 |
+
"epoch": 0.02,
|
1044 |
+
"learning_rate": 4.7791124797650865e-06,
|
1045 |
+
"loss": 1.493,
|
1046 |
+
"step": 740
|
1047 |
+
},
|
1048 |
+
{
|
1049 |
+
"epoch": 0.02,
|
1050 |
+
"learning_rate": 4.788867669692332e-06,
|
1051 |
+
"loss": 1.5065,
|
1052 |
+
"step": 750
|
1053 |
+
},
|
1054 |
+
{
|
1055 |
+
"epoch": 0.02,
|
1056 |
+
"eval_gsm8k_hard_accuracy": 0.9174097145881682,
|
1057 |
+
"eval_gsm8k_hard_loss": 0.366455078125,
|
1058 |
+
"eval_gsm8k_hard_runtime": 6.7984,
|
1059 |
+
"eval_gsm8k_hard_samples_per_second": 38.833,
|
1060 |
+
"eval_gsm8k_hard_steps_per_second": 0.441,
|
1061 |
+
"step": 750
|
1062 |
+
},
|
1063 |
+
{
|
1064 |
+
"epoch": 0.02,
|
1065 |
+
"eval_webgpt_accuracy": 0.5023221414992414,
|
1066 |
+
"eval_webgpt_loss": 2.181640625,
|
1067 |
+
"eval_webgpt_runtime": 39.4537,
|
1068 |
+
"eval_webgpt_samples_per_second": 99.256,
|
1069 |
+
"eval_webgpt_steps_per_second": 1.039,
|
1070 |
+
"step": 750
|
1071 |
+
},
|
1072 |
+
{
|
1073 |
+
"epoch": 0.02,
|
1074 |
+
"eval_squad_v2_accuracy": 0.8977014895925817,
|
1075 |
+
"eval_squad_v2_loss": 0.331787109375,
|
1076 |
+
"eval_squad_v2_runtime": 214.9281,
|
1077 |
+
"eval_squad_v2_samples_per_second": 121.268,
|
1078 |
+
"eval_squad_v2_steps_per_second": 1.266,
|
1079 |
+
"step": 750
|
1080 |
+
},
|
1081 |
+
{
|
1082 |
+
"epoch": 0.02,
|
1083 |
+
"eval_adversarial_qa_accuracy": 0.8063639891346527,
|
1084 |
+
"eval_adversarial_qa_loss": 0.8232421875,
|
1085 |
+
"eval_adversarial_qa_runtime": 51.9182,
|
1086 |
+
"eval_adversarial_qa_samples_per_second": 115.567,
|
1087 |
+
"eval_adversarial_qa_steps_per_second": 1.213,
|
1088 |
+
"step": 750
|
1089 |
+
},
|
1090 |
+
{
|
1091 |
+
"epoch": 0.02,
|
1092 |
+
"eval_private_tuning_accuracy": 0.6775308778615678,
|
1093 |
+
"eval_private_tuning_loss": 1.1962890625,
|
1094 |
+
"eval_private_tuning_runtime": 149.5702,
|
1095 |
+
"eval_private_tuning_samples_per_second": 141.592,
|
1096 |
+
"eval_private_tuning_steps_per_second": 1.478,
|
1097 |
+
"step": 750
|
1098 |
+
},
|
1099 |
+
{
|
1100 |
+
"epoch": 0.02,
|
1101 |
+
"eval_oa_translated_accuracy": 0.6986534506008611,
|
1102 |
+
"eval_oa_translated_loss": 1.22265625,
|
1103 |
+
"eval_oa_translated_runtime": 1324.5514,
|
1104 |
+
"eval_oa_translated_samples_per_second": 89.655,
|
1105 |
+
"eval_oa_translated_steps_per_second": 0.935,
|
1106 |
+
"step": 750
|
1107 |
+
},
|
1108 |
+
{
|
1109 |
+
"epoch": 0.02,
|
1110 |
+
"eval_prosocial_dialogue_accuracy": 0.5327101026505052,
|
1111 |
+
"eval_prosocial_dialogue_loss": 1.7802734375,
|
1112 |
+
"eval_prosocial_dialogue_runtime": 70.7166,
|
1113 |
+
"eval_prosocial_dialogue_samples_per_second": 381.565,
|
1114 |
+
"eval_prosocial_dialogue_steps_per_second": 3.988,
|
1115 |
+
"step": 750
|
1116 |
+
},
|
1117 |
+
{
|
1118 |
+
"epoch": 0.02,
|
1119 |
+
"eval_math_qa_accuracy": 0.5798378605476227,
|
1120 |
+
"eval_math_qa_loss": 1.826171875,
|
1121 |
+
"eval_math_qa_runtime": 44.6748,
|
1122 |
+
"eval_math_qa_samples_per_second": 133.588,
|
1123 |
+
"eval_math_qa_steps_per_second": 1.41,
|
1124 |
+
"step": 750
|
1125 |
+
},
|
1126 |
+
{
|
1127 |
+
"epoch": 0.02,
|
1128 |
+
"eval_wikihow_accuracy": 0.6193731798640966,
|
1129 |
+
"eval_wikihow_loss": 1.802734375,
|
1130 |
+
"eval_wikihow_runtime": 16.8626,
|
1131 |
+
"eval_wikihow_samples_per_second": 135.981,
|
1132 |
+
"eval_wikihow_steps_per_second": 1.423,
|
1133 |
+
"step": 750
|
1134 |
+
},
|
1135 |
+
{
|
1136 |
+
"epoch": 0.02,
|
1137 |
+
"eval_joke_accuracy": 0.5020849128127369,
|
1138 |
+
"eval_joke_loss": 2.1640625,
|
1139 |
+
"eval_joke_runtime": 1.3597,
|
1140 |
+
"eval_joke_samples_per_second": 55.896,
|
1141 |
+
"eval_joke_steps_per_second": 0.735,
|
1142 |
+
"step": 750
|
1143 |
+
},
|
1144 |
+
{
|
1145 |
+
"epoch": 0.02,
|
1146 |
+
"eval_gsm8k_accuracy": 0.760008955934006,
|
1147 |
+
"eval_gsm8k_loss": 0.9189453125,
|
1148 |
+
"eval_gsm8k_runtime": 12.0443,
|
1149 |
+
"eval_gsm8k_samples_per_second": 124.126,
|
1150 |
+
"eval_gsm8k_steps_per_second": 1.328,
|
1151 |
+
"step": 750
|
1152 |
+
},
|
1153 |
+
{
|
1154 |
+
"epoch": 0.02,
|
1155 |
+
"eval_ted_trans_en-hi_accuracy": 0.6714796661809511,
|
1156 |
+
"eval_ted_trans_en-hi_loss": 1.2548828125,
|
1157 |
+
"eval_ted_trans_en-hi_runtime": 2.3695,
|
1158 |
+
"eval_ted_trans_en-hi_samples_per_second": 43.47,
|
1159 |
+
"eval_ted_trans_en-hi_steps_per_second": 0.844,
|
1160 |
+
"step": 750
|
1161 |
+
},
|
1162 |
+
{
|
1163 |
+
"epoch": 0.02,
|
1164 |
+
"eval_ted_trans_de-ja_accuracy": 0.6580367185861629,
|
1165 |
+
"eval_ted_trans_de-ja_loss": 1.466796875,
|
1166 |
+
"eval_ted_trans_de-ja_runtime": 9.4824,
|
1167 |
+
"eval_ted_trans_de-ja_samples_per_second": 75.72,
|
1168 |
+
"eval_ted_trans_de-ja_steps_per_second": 0.844,
|
1169 |
+
"step": 750
|
1170 |
+
},
|
1171 |
+
{
|
1172 |
+
"epoch": 0.02,
|
1173 |
+
"eval_ted_trans_nl-en_accuracy": 0.749224515991015,
|
1174 |
+
"eval_ted_trans_nl-en_loss": 1.080078125,
|
1175 |
+
"eval_ted_trans_nl-en_runtime": 8.4451,
|
1176 |
+
"eval_ted_trans_nl-en_samples_per_second": 91.296,
|
1177 |
+
"eval_ted_trans_nl-en_steps_per_second": 1.066,
|
1178 |
+
"step": 750
|
1179 |
+
},
|
1180 |
+
{
|
1181 |
+
"epoch": 0.02,
|
1182 |
+
"eval_ted_trans_en-ja_accuracy": 0.6621738060068931,
|
1183 |
+
"eval_ted_trans_en-ja_loss": 1.384765625,
|
1184 |
+
"eval_ted_trans_en-ja_runtime": 10.0893,
|
1185 |
+
"eval_ted_trans_en-ja_samples_per_second": 79.391,
|
1186 |
+
"eval_ted_trans_en-ja_steps_per_second": 0.892,
|
1187 |
+
"step": 750
|
1188 |
+
},
|
1189 |
+
{
|
1190 |
+
"epoch": 0.02,
|
1191 |
+
"eval_ted_trans_en-es_accuracy": 0.793457991028678,
|
1192 |
+
"eval_ted_trans_en-es_loss": 0.85205078125,
|
1193 |
+
"eval_ted_trans_en-es_runtime": 7.1771,
|
1194 |
+
"eval_ted_trans_en-es_samples_per_second": 115.088,
|
1195 |
+
"eval_ted_trans_en-es_steps_per_second": 1.254,
|
1196 |
+
"step": 750
|
1197 |
+
},
|
1198 |
+
{
|
1199 |
+
"epoch": 0.02,
|
1200 |
+
"eval_ted_trans_en-ms_accuracy": 0.6782511210762332,
|
1201 |
+
"eval_ted_trans_en-ms_loss": 1.4208984375,
|
1202 |
+
"eval_ted_trans_en-ms_runtime": 2.0842,
|
1203 |
+
"eval_ted_trans_en-ms_samples_per_second": 20.151,
|
1204 |
+
"eval_ted_trans_en-ms_steps_per_second": 0.48,
|
1205 |
+
"step": 750
|
1206 |
+
},
|
1207 |
+
{
|
1208 |
+
"epoch": 0.02,
|
1209 |
+
"eval_xsum_accuracy": 0.6225130561751453,
|
1210 |
+
"eval_xsum_loss": 1.4462890625,
|
1211 |
+
"eval_xsum_runtime": 439.444,
|
1212 |
+
"eval_xsum_samples_per_second": 92.865,
|
1213 |
+
"eval_xsum_steps_per_second": 0.969,
|
1214 |
+
"step": 750
|
1215 |
+
},
|
1216 |
+
{
|
1217 |
+
"epoch": 0.02,
|
1218 |
+
"eval_cnn_dailymail_accuracy": 0.6778638530242029,
|
1219 |
+
"eval_cnn_dailymail_loss": NaN,
|
1220 |
+
"eval_cnn_dailymail_runtime": 633.9568,
|
1221 |
+
"eval_cnn_dailymail_samples_per_second": 90.579,
|
1222 |
+
"eval_cnn_dailymail_steps_per_second": 0.945,
|
1223 |
+
"step": 750
|
1224 |
+
},
|
1225 |
+
{
|
1226 |
+
"epoch": 0.02,
|
1227 |
+
"eval_multi_news_accuracy": 0.5553791439095643,
|
1228 |
+
"eval_multi_news_loss": NaN,
|
1229 |
+
"eval_multi_news_runtime": 103.0316,
|
1230 |
+
"eval_multi_news_samples_per_second": 87.303,
|
1231 |
+
"eval_multi_news_steps_per_second": 0.912,
|
1232 |
+
"step": 750
|
1233 |
+
},
|
1234 |
+
{
|
1235 |
+
"epoch": 0.02,
|
1236 |
+
"eval_tldr_news_accuracy": 0.5591084360011286,
|
1237 |
+
"eval_tldr_news_loss": 1.9892578125,
|
1238 |
+
"eval_tldr_news_runtime": 8.3367,
|
1239 |
+
"eval_tldr_news_samples_per_second": 171.29,
|
1240 |
+
"eval_tldr_news_steps_per_second": 1.799,
|
1241 |
+
"step": 750
|
1242 |
+
},
|
1243 |
+
{
|
1244 |
+
"epoch": 0.02,
|
1245 |
+
"eval_scitldr_accuracy": 0.49270664505672607,
|
1246 |
+
"eval_scitldr_loss": NaN,
|
1247 |
+
"eval_scitldr_runtime": 5.8517,
|
1248 |
+
"eval_scitldr_samples_per_second": 68.186,
|
1249 |
+
"eval_scitldr_steps_per_second": 0.854,
|
1250 |
+
"step": 750
|
1251 |
+
},
|
1252 |
+
{
|
1253 |
+
"epoch": 0.02,
|
1254 |
+
"eval_samsum_accuracy": 0.6411875245035082,
|
1255 |
+
"eval_samsum_loss": 1.32421875,
|
1256 |
+
"eval_samsum_runtime": 32.2591,
|
1257 |
+
"eval_samsum_samples_per_second": 91.354,
|
1258 |
+
"eval_samsum_steps_per_second": 0.961,
|
1259 |
+
"step": 750
|
1260 |
+
},
|
1261 |
+
{
|
1262 |
+
"epoch": 0.02,
|
1263 |
+
"eval_debate_sum_accuracy": 0.9381249710591028,
|
1264 |
+
"eval_debate_sum_loss": 0.337646484375,
|
1265 |
+
"eval_debate_sum_runtime": 548.1225,
|
1266 |
+
"eval_debate_sum_samples_per_second": 87.78,
|
1267 |
+
"eval_debate_sum_steps_per_second": 0.916,
|
1268 |
+
"step": 750
|
1269 |
+
},
|
1270 |
+
{
|
1271 |
+
"epoch": 0.02,
|
1272 |
+
"eval_billsum_accuracy": 0.6810246806233696,
|
1273 |
+
"eval_billsum_loss": 1.3359375,
|
1274 |
+
"eval_billsum_runtime": 50.0247,
|
1275 |
+
"eval_billsum_samples_per_second": 75.763,
|
1276 |
+
"eval_billsum_steps_per_second": 0.8,
|
1277 |
+
"step": 750
|
1278 |
+
},
|
1279 |
+
{
|
1280 |
+
"epoch": 0.02,
|
1281 |
+
"eval_wmt2019_zh-en_accuracy": 0.6683125468349724,
|
1282 |
+
"eval_wmt2019_zh-en_loss": 1.451171875,
|
1283 |
+
"eval_wmt2019_zh-en_runtime": 27.2087,
|
1284 |
+
"eval_wmt2019_zh-en_samples_per_second": 146.313,
|
1285 |
+
"eval_wmt2019_zh-en_steps_per_second": 1.544,
|
1286 |
+
"step": 750
|
1287 |
+
},
|
1288 |
+
{
|
1289 |
+
"epoch": 0.02,
|
1290 |
+
"eval_wmt2019_ru-en_accuracy": 0.755552089368213,
|
1291 |
+
"eval_wmt2019_ru-en_loss": 0.94091796875,
|
1292 |
+
"eval_wmt2019_ru-en_runtime": 20.7954,
|
1293 |
+
"eval_wmt2019_ru-en_samples_per_second": 144.262,
|
1294 |
+
"eval_wmt2019_ru-en_steps_per_second": 1.539,
|
1295 |
+
"step": 750
|
1296 |
+
},
|
1297 |
+
{
|
1298 |
+
"epoch": 0.02,
|
1299 |
+
"eval_wmt2019_de-en_accuracy": 0.7641599453590333,
|
1300 |
+
"eval_wmt2019_de-en_loss": 0.9228515625,
|
1301 |
+
"eval_wmt2019_de-en_runtime": 15.5528,
|
1302 |
+
"eval_wmt2019_de-en_samples_per_second": 192.762,
|
1303 |
+
"eval_wmt2019_de-en_steps_per_second": 2.058,
|
1304 |
+
"step": 750
|
1305 |
+
},
|
1306 |
+
{
|
1307 |
+
"epoch": 0.02,
|
1308 |
+
"eval_wmt2019_fr-de_accuracy": 0.7474449624849476,
|
1309 |
+
"eval_wmt2019_fr-de_loss": 1.00390625,
|
1310 |
+
"eval_wmt2019_fr-de_runtime": 11.5093,
|
1311 |
+
"eval_wmt2019_fr-de_samples_per_second": 131.372,
|
1312 |
+
"eval_wmt2019_fr-de_steps_per_second": 1.39,
|
1313 |
+
"step": 750
|
1314 |
+
},
|
1315 |
+
{
|
1316 |
+
"epoch": 0.02,
|
1317 |
+
"eval_essay_instruction_accuracy": 0.6032218119098689,
|
1318 |
+
"eval_essay_instruction_loss": 1.904296875,
|
1319 |
+
"eval_essay_instruction_runtime": 7.606,
|
1320 |
+
"eval_essay_instruction_samples_per_second": 54.299,
|
1321 |
+
"eval_essay_instruction_steps_per_second": 0.657,
|
1322 |
+
"step": 750
|
1323 |
+
},
|
1324 |
+
{
|
1325 |
+
"epoch": 0.02,
|
1326 |
+
"eval_reddit_eli5_accuracy": 0.4612608360817972,
|
1327 |
+
"eval_reddit_eli5_loss": 2.431640625,
|
1328 |
+
"eval_reddit_eli5_runtime": 597.1988,
|
1329 |
+
"eval_reddit_eli5_samples_per_second": 91.305,
|
1330 |
+
"eval_reddit_eli5_steps_per_second": 0.951,
|
1331 |
+
"step": 750
|
1332 |
+
},
|
1333 |
+
{
|
1334 |
+
"epoch": 0.02,
|
1335 |
+
"eval_reddit_askh_accuracy": 0.46371300245115404,
|
1336 |
+
"eval_reddit_askh_loss": 2.525390625,
|
1337 |
+
"eval_reddit_askh_runtime": 253.0373,
|
1338 |
+
"eval_reddit_askh_samples_per_second": 77.874,
|
1339 |
+
"eval_reddit_askh_steps_per_second": 0.814,
|
1340 |
+
"step": 750
|
1341 |
+
},
|
1342 |
+
{
|
1343 |
+
"epoch": 0.02,
|
1344 |
+
"eval_reddit_asks_accuracy": 0.47195547000535765,
|
1345 |
+
"eval_reddit_asks_loss": 2.388671875,
|
1346 |
+
"eval_reddit_asks_runtime": 304.1555,
|
1347 |
+
"eval_reddit_asks_samples_per_second": 86.653,
|
1348 |
+
"eval_reddit_asks_steps_per_second": 0.904,
|
1349 |
+
"step": 750
|
1350 |
+
},
|
1351 |
+
{
|
1352 |
+
"epoch": 0.02,
|
1353 |
+
"learning_rate": 4.798493132500121e-06,
|
1354 |
+
"loss": 1.5526,
|
1355 |
+
"step": 760
|
1356 |
+
},
|
1357 |
+
{
|
1358 |
+
"epoch": 0.02,
|
1359 |
+
"learning_rate": 4.8079922732483016e-06,
|
1360 |
+
"loss": 1.4845,
|
1361 |
+
"step": 770
|
1362 |
+
},
|
1363 |
+
{
|
1364 |
+
"epoch": 0.02,
|
1365 |
+
"learning_rate": 4.817368364668191e-06,
|
1366 |
+
"loss": 1.5351,
|
1367 |
+
"step": 780
|
1368 |
+
},
|
1369 |
+
{
|
1370 |
+
"epoch": 0.02,
|
1371 |
+
"learning_rate": 4.8266245539317745e-06,
|
1372 |
+
"loss": 1.5942,
|
1373 |
+
"step": 790
|
1374 |
+
},
|
1375 |
+
{
|
1376 |
+
"epoch": 0.02,
|
1377 |
+
"learning_rate": 4.835763868993521e-06,
|
1378 |
+
"loss": 1.4886,
|
1379 |
+
"step": 800
|
1380 |
+
},
|
1381 |
+
{
|
1382 |
+
"epoch": 0.02,
|
1383 |
+
"learning_rate": 4.844789224536785e-06,
|
1384 |
+
"loss": 1.5645,
|
1385 |
+
"step": 810
|
1386 |
+
},
|
1387 |
+
{
|
1388 |
+
"epoch": 0.02,
|
1389 |
+
"learning_rate": 4.853703427554027e-06,
|
1390 |
+
"loss": 1.5099,
|
1391 |
+
"step": 820
|
1392 |
+
},
|
1393 |
+
{
|
1394 |
+
"epoch": 0.02,
|
1395 |
+
"learning_rate": 4.862509182587578e-06,
|
1396 |
+
"loss": 1.619,
|
1397 |
+
"step": 830
|
1398 |
+
},
|
1399 |
+
{
|
1400 |
+
"epoch": 0.02,
|
1401 |
+
"learning_rate": 4.871209096655434e-06,
|
1402 |
+
"loss": 1.542,
|
1403 |
+
"step": 840
|
1404 |
+
},
|
1405 |
+
{
|
1406 |
+
"epoch": 0.03,
|
1407 |
+
"learning_rate": 4.879805683884512e-06,
|
1408 |
+
"loss": 1.5254,
|
1409 |
+
"step": 850
|
1410 |
+
},
|
1411 |
+
{
|
1412 |
+
"epoch": 0.03,
|
1413 |
+
"learning_rate": 4.888301369871998e-06,
|
1414 |
+
"loss": 1.5427,
|
1415 |
+
"step": 860
|
1416 |
+
},
|
1417 |
+
{
|
1418 |
+
"epoch": 0.03,
|
1419 |
+
"learning_rate": 4.8966984957936845e-06,
|
1420 |
+
"loss": 1.5403,
|
1421 |
+
"step": 870
|
1422 |
+
},
|
1423 |
+
{
|
1424 |
+
"epoch": 0.03,
|
1425 |
+
"learning_rate": 4.904999322276735e-06,
|
1426 |
+
"loss": 1.5848,
|
1427 |
+
"step": 880
|
1428 |
+
},
|
1429 |
+
{
|
1430 |
+
"epoch": 0.03,
|
1431 |
+
"learning_rate": 4.913206033052878e-06,
|
1432 |
+
"loss": 1.5205,
|
1433 |
+
"step": 890
|
1434 |
+
},
|
1435 |
+
{
|
1436 |
+
"epoch": 0.03,
|
1437 |
+
"learning_rate": 4.921320738406821e-06,
|
1438 |
+
"loss": 1.5359,
|
1439 |
+
"step": 900
|
1440 |
+
},
|
1441 |
+
{
|
1442 |
+
"epoch": 0.03,
|
1443 |
+
"learning_rate": 4.929345478433492e-06,
|
1444 |
+
"loss": 1.5631,
|
1445 |
+
"step": 910
|
1446 |
+
},
|
1447 |
+
{
|
1448 |
+
"epoch": 0.03,
|
1449 |
+
"learning_rate": 4.937282226116702e-06,
|
1450 |
+
"loss": 1.5928,
|
1451 |
+
"step": 920
|
1452 |
+
},
|
1453 |
+
{
|
1454 |
+
"epoch": 0.03,
|
1455 |
+
"learning_rate": 4.945132890240829e-06,
|
1456 |
+
"loss": 1.4707,
|
1457 |
+
"step": 930
|
1458 |
+
},
|
1459 |
+
{
|
1460 |
+
"epoch": 0.03,
|
1461 |
+
"learning_rate": 4.952899318146298e-06,
|
1462 |
+
"loss": 1.5279,
|
1463 |
+
"step": 940
|
1464 |
+
},
|
1465 |
+
{
|
1466 |
+
"epoch": 0.03,
|
1467 |
+
"learning_rate": 4.96058329833879e-06,
|
1468 |
+
"loss": 1.5411,
|
1469 |
+
"step": 950
|
1470 |
+
},
|
1471 |
+
{
|
1472 |
+
"epoch": 0.03,
|
1473 |
+
"learning_rate": 4.968186562961406e-06,
|
1474 |
+
"loss": 1.6029,
|
1475 |
+
"step": 960
|
1476 |
+
},
|
1477 |
+
{
|
1478 |
+
"epoch": 0.03,
|
1479 |
+
"learning_rate": 4.975710790138337e-06,
|
1480 |
+
"loss": 1.648,
|
1481 |
+
"step": 970
|
1482 |
+
},
|
1483 |
+
{
|
1484 |
+
"epoch": 0.03,
|
1485 |
+
"learning_rate": 4.9831576061979556e-06,
|
1486 |
+
"loss": 1.5799,
|
1487 |
+
"step": 980
|
1488 |
+
},
|
1489 |
+
{
|
1490 |
+
"epoch": 0.03,
|
1491 |
+
"learning_rate": 4.990528587782728e-06,
|
1492 |
+
"loss": 1.5592,
|
1493 |
+
"step": 990
|
1494 |
+
},
|
1495 |
+
{
|
1496 |
+
"epoch": 0.03,
|
1497 |
+
"learning_rate": 4.99782526385276e-06,
|
1498 |
+
"loss": 1.6317,
|
1499 |
+
"step": 1000
|
1500 |
+
},
|
1501 |
+
{
|
1502 |
+
"epoch": 0.03,
|
1503 |
+
"eval_gsm8k_hard_accuracy": 0.9242294694841415,
|
1504 |
+
"eval_gsm8k_hard_loss": 0.337158203125,
|
1505 |
+
"eval_gsm8k_hard_runtime": 4.4214,
|
1506 |
+
"eval_gsm8k_hard_samples_per_second": 59.709,
|
1507 |
+
"eval_gsm8k_hard_steps_per_second": 0.679,
|
1508 |
+
"step": 1000
|
1509 |
+
},
|
1510 |
+
{
|
1511 |
+
"epoch": 0.03,
|
1512 |
+
"eval_webgpt_accuracy": 0.5016719087887306,
|
1513 |
+
"eval_webgpt_loss": 2.181640625,
|
1514 |
+
"eval_webgpt_runtime": 36.3649,
|
1515 |
+
"eval_webgpt_samples_per_second": 107.686,
|
1516 |
+
"eval_webgpt_steps_per_second": 1.127,
|
1517 |
+
"step": 1000
|
1518 |
+
},
|
1519 |
+
{
|
1520 |
+
"epoch": 0.03,
|
1521 |
+
"eval_squad_v2_accuracy": 0.9092151805972463,
|
1522 |
+
"eval_squad_v2_loss": 0.35546875,
|
1523 |
+
"eval_squad_v2_runtime": 216.2111,
|
1524 |
+
"eval_squad_v2_samples_per_second": 120.549,
|
1525 |
+
"eval_squad_v2_steps_per_second": 1.258,
|
1526 |
+
"step": 1000
|
1527 |
+
},
|
1528 |
+
{
|
1529 |
+
"epoch": 0.03,
|
1530 |
+
"eval_adversarial_qa_accuracy": 0.8333781081161756,
|
1531 |
+
"eval_adversarial_qa_loss": 0.83642578125,
|
1532 |
+
"eval_adversarial_qa_runtime": 52.2959,
|
1533 |
+
"eval_adversarial_qa_samples_per_second": 114.732,
|
1534 |
+
"eval_adversarial_qa_steps_per_second": 1.205,
|
1535 |
+
"step": 1000
|
1536 |
+
},
|
1537 |
+
{
|
1538 |
+
"epoch": 0.03,
|
1539 |
+
"eval_private_tuning_accuracy": 0.6788522917969135,
|
1540 |
+
"eval_private_tuning_loss": 1.1845703125,
|
1541 |
+
"eval_private_tuning_runtime": 145.6236,
|
1542 |
+
"eval_private_tuning_samples_per_second": 145.43,
|
1543 |
+
"eval_private_tuning_steps_per_second": 1.518,
|
1544 |
+
"step": 1000
|
1545 |
+
},
|
1546 |
+
{
|
1547 |
+
"epoch": 0.03,
|
1548 |
+
"eval_oa_translated_accuracy": 0.7015835515263078,
|
1549 |
+
"eval_oa_translated_loss": 1.208984375,
|
1550 |
+
"eval_oa_translated_runtime": 1331.5436,
|
1551 |
+
"eval_oa_translated_samples_per_second": 89.184,
|
1552 |
+
"eval_oa_translated_steps_per_second": 0.93,
|
1553 |
+
"step": 1000
|
1554 |
+
},
|
1555 |
+
{
|
1556 |
+
"epoch": 0.03,
|
1557 |
+
"eval_prosocial_dialogue_accuracy": 0.5440172516743936,
|
1558 |
+
"eval_prosocial_dialogue_loss": 1.7470703125,
|
1559 |
+
"eval_prosocial_dialogue_runtime": 66.8792,
|
1560 |
+
"eval_prosocial_dialogue_samples_per_second": 403.459,
|
1561 |
+
"eval_prosocial_dialogue_steps_per_second": 4.217,
|
1562 |
+
"step": 1000
|
1563 |
+
},
|
1564 |
+
{
|
1565 |
+
"epoch": 0.03,
|
1566 |
+
"eval_math_qa_accuracy": 0.5903696634283728,
|
1567 |
+
"eval_math_qa_loss": 1.7734375,
|
1568 |
+
"eval_math_qa_runtime": 43.3917,
|
1569 |
+
"eval_math_qa_samples_per_second": 137.538,
|
1570 |
+
"eval_math_qa_steps_per_second": 1.452,
|
1571 |
+
"step": 1000
|
1572 |
+
},
|
1573 |
+
{
|
1574 |
+
"epoch": 0.03,
|
1575 |
+
"eval_wikihow_accuracy": 0.6181528220773818,
|
1576 |
+
"eval_wikihow_loss": 1.79296875,
|
1577 |
+
"eval_wikihow_runtime": 16.8686,
|
1578 |
+
"eval_wikihow_samples_per_second": 135.933,
|
1579 |
+
"eval_wikihow_steps_per_second": 1.423,
|
1580 |
+
"step": 1000
|
1581 |
+
},
|
1582 |
+
{
|
1583 |
+
"epoch": 0.03,
|
1584 |
+
"eval_joke_accuracy": 0.5162054586808188,
|
1585 |
+
"eval_joke_loss": 2.095703125,
|
1586 |
+
"eval_joke_runtime": 1.1499,
|
1587 |
+
"eval_joke_samples_per_second": 66.094,
|
1588 |
+
"eval_joke_steps_per_second": 0.87,
|
1589 |
+
"step": 1000
|
1590 |
+
},
|
1591 |
+
{
|
1592 |
+
"epoch": 0.03,
|
1593 |
+
"eval_gsm8k_accuracy": 0.7709449909740977,
|
1594 |
+
"eval_gsm8k_loss": 0.8671875,
|
1595 |
+
"eval_gsm8k_runtime": 11.5578,
|
1596 |
+
"eval_gsm8k_samples_per_second": 129.35,
|
1597 |
+
"eval_gsm8k_steps_per_second": 1.384,
|
1598 |
+
"step": 1000
|
1599 |
+
},
|
1600 |
+
{
|
1601 |
+
"epoch": 0.03,
|
1602 |
+
"eval_ted_trans_en-hi_accuracy": 0.6727249123718032,
|
1603 |
+
"eval_ted_trans_en-hi_loss": 1.2490234375,
|
1604 |
+
"eval_ted_trans_en-hi_runtime": 3.3114,
|
1605 |
+
"eval_ted_trans_en-hi_samples_per_second": 31.105,
|
1606 |
+
"eval_ted_trans_en-hi_steps_per_second": 0.604,
|
1607 |
+
"step": 1000
|
1608 |
+
},
|
1609 |
+
{
|
1610 |
+
"epoch": 0.03,
|
1611 |
+
"eval_ted_trans_de-ja_accuracy": 0.6605206483545547,
|
1612 |
+
"eval_ted_trans_de-ja_loss": 1.4599609375,
|
1613 |
+
"eval_ted_trans_de-ja_runtime": 8.583,
|
1614 |
+
"eval_ted_trans_de-ja_samples_per_second": 83.654,
|
1615 |
+
"eval_ted_trans_de-ja_steps_per_second": 0.932,
|
1616 |
+
"step": 1000
|
1617 |
+
},
|
1618 |
+
{
|
1619 |
+
"epoch": 0.03,
|
1620 |
+
"eval_ted_trans_nl-en_accuracy": 0.757177992835374,
|
1621 |
+
"eval_ted_trans_nl-en_loss": 1.0478515625,
|
1622 |
+
"eval_ted_trans_nl-en_runtime": 8.7612,
|
1623 |
+
"eval_ted_trans_nl-en_samples_per_second": 88.002,
|
1624 |
+
"eval_ted_trans_nl-en_steps_per_second": 1.027,
|
1625 |
+
"step": 1000
|
1626 |
+
},
|
1627 |
+
{
|
1628 |
+
"epoch": 0.03,
|
1629 |
+
"eval_ted_trans_en-ja_accuracy": 0.6644915715062534,
|
1630 |
+
"eval_ted_trans_en-ja_loss": 1.3798828125,
|
1631 |
+
"eval_ted_trans_en-ja_runtime": 9.6809,
|
1632 |
+
"eval_ted_trans_en-ja_samples_per_second": 82.74,
|
1633 |
+
"eval_ted_trans_en-ja_steps_per_second": 0.93,
|
1634 |
+
"step": 1000
|
1635 |
+
},
|
1636 |
+
{
|
1637 |
+
"epoch": 0.03,
|
1638 |
+
"eval_ted_trans_en-es_accuracy": 0.7831230683487865,
|
1639 |
+
"eval_ted_trans_en-es_loss": 0.89501953125,
|
1640 |
+
"eval_ted_trans_en-es_runtime": 8.1422,
|
1641 |
+
"eval_ted_trans_en-es_samples_per_second": 101.447,
|
1642 |
+
"eval_ted_trans_en-es_steps_per_second": 1.105,
|
1643 |
+
"step": 1000
|
1644 |
+
},
|
1645 |
+
{
|
1646 |
+
"epoch": 0.03,
|
1647 |
+
"eval_ted_trans_en-ms_accuracy": 0.6917040358744395,
|
1648 |
+
"eval_ted_trans_en-ms_loss": 1.3955078125,
|
1649 |
+
"eval_ted_trans_en-ms_runtime": 0.7332,
|
1650 |
+
"eval_ted_trans_en-ms_samples_per_second": 57.285,
|
1651 |
+
"eval_ted_trans_en-ms_steps_per_second": 1.364,
|
1652 |
+
"step": 1000
|
1653 |
+
},
|
1654 |
+
{
|
1655 |
+
"epoch": 0.03,
|
1656 |
+
"eval_xsum_accuracy": 0.6225837900623918,
|
1657 |
+
"eval_xsum_loss": 1.4453125,
|
1658 |
+
"eval_xsum_runtime": 443.13,
|
1659 |
+
"eval_xsum_samples_per_second": 92.093,
|
1660 |
+
"eval_xsum_steps_per_second": 0.961,
|
1661 |
+
"step": 1000
|
1662 |
+
},
|
1663 |
+
{
|
1664 |
+
"epoch": 0.03,
|
1665 |
+
"eval_cnn_dailymail_accuracy": 0.6811569253551761,
|
1666 |
+
"eval_cnn_dailymail_loss": NaN,
|
1667 |
+
"eval_cnn_dailymail_runtime": 634.279,
|
1668 |
+
"eval_cnn_dailymail_samples_per_second": 90.533,
|
1669 |
+
"eval_cnn_dailymail_steps_per_second": 0.944,
|
1670 |
+
"step": 1000
|
1671 |
+
},
|
1672 |
+
{
|
1673 |
+
"epoch": 0.03,
|
1674 |
+
"eval_multi_news_accuracy": 0.5572843896862695,
|
1675 |
+
"eval_multi_news_loss": NaN,
|
1676 |
+
"eval_multi_news_runtime": 104.4536,
|
1677 |
+
"eval_multi_news_samples_per_second": 86.115,
|
1678 |
+
"eval_multi_news_steps_per_second": 0.9,
|
1679 |
+
"step": 1000
|
1680 |
+
},
|
1681 |
+
{
|
1682 |
+
"epoch": 0.03,
|
1683 |
+
"eval_tldr_news_accuracy": 0.5934825543120474,
|
1684 |
+
"eval_tldr_news_loss": 1.779296875,
|
1685 |
+
"eval_tldr_news_runtime": 7.875,
|
1686 |
+
"eval_tldr_news_samples_per_second": 181.334,
|
1687 |
+
"eval_tldr_news_steps_per_second": 1.905,
|
1688 |
+
"step": 1000
|
1689 |
+
},
|
1690 |
+
{
|
1691 |
+
"epoch": 0.03,
|
1692 |
+
"eval_scitldr_accuracy": 0.49756888168557534,
|
1693 |
+
"eval_scitldr_loss": NaN,
|
1694 |
+
"eval_scitldr_runtime": 5.4836,
|
1695 |
+
"eval_scitldr_samples_per_second": 72.763,
|
1696 |
+
"eval_scitldr_steps_per_second": 0.912,
|
1697 |
+
"step": 1000
|
1698 |
+
},
|
1699 |
+
{
|
1700 |
+
"epoch": 0.03,
|
1701 |
+
"eval_samsum_accuracy": 0.6441076667252498,
|
1702 |
+
"eval_samsum_loss": 1.3203125,
|
1703 |
+
"eval_samsum_runtime": 31.9228,
|
1704 |
+
"eval_samsum_samples_per_second": 92.317,
|
1705 |
+
"eval_samsum_steps_per_second": 0.971,
|
1706 |
+
"step": 1000
|
1707 |
+
},
|
1708 |
+
{
|
1709 |
+
"epoch": 0.03,
|
1710 |
+
"eval_debate_sum_accuracy": 0.9393930900916929,
|
1711 |
+
"eval_debate_sum_loss": 0.327392578125,
|
1712 |
+
"eval_debate_sum_runtime": 546.4353,
|
1713 |
+
"eval_debate_sum_samples_per_second": 88.051,
|
1714 |
+
"eval_debate_sum_steps_per_second": 0.919,
|
1715 |
+
"step": 1000
|
1716 |
+
},
|
1717 |
+
{
|
1718 |
+
"epoch": 0.03,
|
1719 |
+
"eval_billsum_accuracy": 0.6859647270039075,
|
1720 |
+
"eval_billsum_loss": 1.3212890625,
|
1721 |
+
"eval_billsum_runtime": 47.3064,
|
1722 |
+
"eval_billsum_samples_per_second": 80.116,
|
1723 |
+
"eval_billsum_steps_per_second": 0.846,
|
1724 |
+
"step": 1000
|
1725 |
+
},
|
1726 |
+
{
|
1727 |
+
"epoch": 0.03,
|
1728 |
+
"eval_wmt2019_zh-en_accuracy": 0.6666222464280335,
|
1729 |
+
"eval_wmt2019_zh-en_loss": 1.4609375,
|
1730 |
+
"eval_wmt2019_zh-en_runtime": 27.4142,
|
1731 |
+
"eval_wmt2019_zh-en_samples_per_second": 145.217,
|
1732 |
+
"eval_wmt2019_zh-en_steps_per_second": 1.532,
|
1733 |
+
"step": 1000
|
1734 |
+
},
|
1735 |
+
{
|
1736 |
+
"epoch": 0.03,
|
1737 |
+
"eval_wmt2019_ru-en_accuracy": 0.7586163428740916,
|
1738 |
+
"eval_wmt2019_ru-en_loss": 0.93212890625,
|
1739 |
+
"eval_wmt2019_ru-en_runtime": 22.6757,
|
1740 |
+
"eval_wmt2019_ru-en_samples_per_second": 132.3,
|
1741 |
+
"eval_wmt2019_ru-en_steps_per_second": 1.411,
|
1742 |
+
"step": 1000
|
1743 |
+
},
|
1744 |
+
{
|
1745 |
+
"epoch": 0.03,
|
1746 |
+
"eval_wmt2019_de-en_accuracy": 0.7644713185146496,
|
1747 |
+
"eval_wmt2019_de-en_loss": 0.92724609375,
|
1748 |
+
"eval_wmt2019_de-en_runtime": 15.456,
|
1749 |
+
"eval_wmt2019_de-en_samples_per_second": 193.97,
|
1750 |
+
"eval_wmt2019_de-en_steps_per_second": 2.07,
|
1751 |
+
"step": 1000
|
1752 |
+
},
|
1753 |
+
{
|
1754 |
+
"epoch": 0.03,
|
1755 |
+
"eval_wmt2019_fr-de_accuracy": 0.7478946231915353,
|
1756 |
+
"eval_wmt2019_fr-de_loss": 1.0068359375,
|
1757 |
+
"eval_wmt2019_fr-de_runtime": 10.3196,
|
1758 |
+
"eval_wmt2019_fr-de_samples_per_second": 146.518,
|
1759 |
+
"eval_wmt2019_fr-de_steps_per_second": 1.55,
|
1760 |
+
"step": 1000
|
1761 |
+
},
|
1762 |
+
{
|
1763 |
+
"epoch": 0.03,
|
1764 |
+
"eval_essay_instruction_accuracy": 0.6048415629215222,
|
1765 |
+
"eval_essay_instruction_loss": 1.8955078125,
|
1766 |
+
"eval_essay_instruction_runtime": 9.0231,
|
1767 |
+
"eval_essay_instruction_samples_per_second": 45.771,
|
1768 |
+
"eval_essay_instruction_steps_per_second": 0.554,
|
1769 |
+
"step": 1000
|
1770 |
+
},
|
1771 |
+
{
|
1772 |
+
"epoch": 0.03,
|
1773 |
+
"eval_reddit_eli5_accuracy": 0.4608785206404607,
|
1774 |
+
"eval_reddit_eli5_loss": 2.4296875,
|
1775 |
+
"eval_reddit_eli5_runtime": 597.6745,
|
1776 |
+
"eval_reddit_eli5_samples_per_second": 91.232,
|
1777 |
+
"eval_reddit_eli5_steps_per_second": 0.95,
|
1778 |
+
"step": 1000
|
1779 |
+
},
|
1780 |
+
{
|
1781 |
+
"epoch": 0.03,
|
1782 |
+
"eval_reddit_askh_accuracy": 0.4638486660338061,
|
1783 |
+
"eval_reddit_askh_loss": 2.5234375,
|
1784 |
+
"eval_reddit_askh_runtime": 248.9187,
|
1785 |
+
"eval_reddit_askh_samples_per_second": 79.162,
|
1786 |
+
"eval_reddit_askh_steps_per_second": 0.828,
|
1787 |
+
"step": 1000
|
1788 |
+
},
|
1789 |
+
{
|
1790 |
+
"epoch": 0.03,
|
1791 |
+
"eval_reddit_asks_accuracy": 0.4715865474658219,
|
1792 |
+
"eval_reddit_asks_loss": 2.384765625,
|
1793 |
+
"eval_reddit_asks_runtime": 310.7333,
|
1794 |
+
"eval_reddit_asks_samples_per_second": 84.819,
|
1795 |
+
"eval_reddit_asks_steps_per_second": 0.885,
|
1796 |
+
"step": 1000
|
1797 |
+
}
|
1798 |
+
],
|
1799 |
+
"max_steps": 67822,
|
1800 |
+
"num_train_epochs": 2,
|
1801 |
+
"total_flos": 1.7293861155088892e+19,
|
1802 |
+
"trial_name": null,
|
1803 |
+
"trial_params": null
|
1804 |
+
}
|