ManthanKulakarni
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Commit
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ManthanKulakarni/Tiny_llama_sql_v1
Browse files- README.md +8 -6
- config.json +15 -22
- generation_config.json +2 -1
- model.safetensors +2 -2
- runs/Jan04_09-14-05_a664a7572be8/events.out.tfevents.1704359672.a664a7572be8.284.0 +3 -0
- runs/Jan04_09-19-52_a664a7572be8/events.out.tfevents.1704360003.a664a7572be8.284.1 +3 -0
- runs/Jan04_09-22-10_a664a7572be8/events.out.tfevents.1704360130.a664a7572be8.474.0 +3 -0
- runs/Jan04_09-23-18_a664a7572be8/events.out.tfevents.1704360198.a664a7572be8.537.0 +3 -0
- runs/Jan04_09-24-20_a664a7572be8/events.out.tfevents.1704360260.a664a7572be8.589.0 +3 -0
- runs/Jan04_09-25-19_a664a7572be8/events.out.tfevents.1704360320.a664a7572be8.648.0 +3 -0
- runs/Jan04_09-29-10_a664a7572be8/events.out.tfevents.1704360551.a664a7572be8.715.0 +3 -0
- runs/Jan04_09-41-42_a664a7572be8/events.out.tfevents.1704361303.a664a7572be8.782.0 +3 -0
- special_tokens_map.json +22 -4
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +32 -10
- training_args.bin +1 -1
README.md
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---
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license: apache-2.0
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base_model:
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tags:
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- generated_from_trainer
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model-index:
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- name: working
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# working
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This model is a fine-tuned version of [
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size:
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.05
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- Transformers 4.36.0
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- Pytorch 2.0.0
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- Datasets 2.1
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- Tokenizers 0.15.0
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---
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license: apache-2.0
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
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tags:
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- trl
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- sft
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- generated_from_trainer
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model-index:
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- name: working
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# working
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This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on an unknown dataset.
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.05
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- Transformers 4.36.0
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- Pytorch 2.0.0
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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config.json
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{
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"_name_or_path": "
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"alibi": true,
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"apply_residual_connection_post_layernorm": false,
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"architectures": [
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"
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],
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"attention_dropout": 0.0,
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"auto_map": {
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"AutoConfig": "tiiuae/falcon-rw-1b--configuration_falcon.FalconConfig",
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"AutoModel": "tiiuae/falcon-rw-1b--modeling_falcon.FalconModel",
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"AutoModelForCausalLM": "tiiuae/falcon-rw-1b--modeling_falcon.FalconForCausalLM",
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"AutoModelForQuestionAnswering": "tiiuae/falcon-rw-1b--modeling_falcon.FalconForQuestionAnswering",
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"AutoModelForSequenceClassification": "tiiuae/falcon-rw-1b--modeling_falcon.FalconForSequenceClassification",
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"AutoModelForTokenClassification": "tiiuae/falcon-rw-1b--modeling_falcon.FalconForTokenClassification"
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},
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"bias": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"
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"
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"new_decoder_architecture": false,
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"num_attention_heads": 32,
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"num_hidden_layers":
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"
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"torch_dtype": "bfloat16",
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"transformers_version": "4.36.0",
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"use_cache": false,
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"vocab_size":
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}
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{
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"_name_or_path": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 5632,
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"max_position_embeddings": 2048,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 22,
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"num_key_value_heads": 4,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.36.0",
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"use_cache": false,
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"vocab_size": 32000
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}
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generation_config.json
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"transformers_version": "4.36.0"
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"transformers_version": "4.36.0"
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}
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model.safetensors
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special_tokens_map.json
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{
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}
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{
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tokenizer.json
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tokenizer.model
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"lstrip": false,
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"chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n' + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
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"sp_model_kwargs": {},
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"tokenizer_class": "LlamaTokenizer",
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"torch_dtype": "auto",
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"unk_token": "<unk>",
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"use_default_system_prompt": false
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}
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training_args.bin
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