Model save

README.md

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+---
+base_model: ondevicellm/tinyllama_moe_v2
+tags:
+- trl
+- sft
+- generated_from_trainer
+datasets:
+- generator
+model-index:
+- name: tinyllama_moe_sft_ultrachat_v2_ep3
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# tinyllama_moe_sft_ultrachat_v2_ep3
+
+This model is a fine-tuned version of [ondevicellm/tinyllama_moe_v2](https://huggingface.co/ondevicellm/tinyllama_moe_v2) on the generator dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1289
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 128
+- total_eval_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 120
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 1.4892        | 0.09  | 100  | 1.4465          |
+| 1.2729        | 0.18  | 200  | 1.2643          |
+| 1.2286        | 0.26  | 300  | 1.2280          |
+| 1.2007        | 0.35  | 400  | 1.2075          |
+| 1.1688        | 0.44  | 500  | 1.1933          |
+| 1.1872        | 0.53  | 600  | 1.1830          |
+| 1.1732        | 0.61  | 700  | 1.1746          |
+| 1.1596        | 0.7   | 800  | 1.1679          |
+| 1.1546        | 0.79  | 900  | 1.1622          |
+| 1.1366        | 0.88  | 1000 | 1.1572          |
+| 1.1606        | 0.96  | 1100 | 1.1527          |
+| 1.0967        | 1.05  | 1200 | 1.1505          |
+| 1.099         | 1.14  | 1300 | 1.1480          |
+| 1.1099        | 1.23  | 1400 | 1.1453          |
+| 1.1015        | 1.31  | 1500 | 1.1432          |
+| 1.104         | 1.4   | 1600 | 1.1408          |
+| 1.0998        | 1.49  | 1700 | 1.1390          |
+| 1.0829        | 1.58  | 1800 | 1.1369          |
+| 1.1052        | 1.66  | 1900 | 1.1353          |
+| 1.1082        | 1.75  | 2000 | 1.1336          |
+| 1.0948        | 1.84  | 2100 | 1.1320          |
+| 1.0682        | 1.93  | 2200 | 1.1308          |
+| 1.0688        | 2.01  | 2300 | 1.1318          |
+| 1.0754        | 2.1   | 2400 | 1.1317          |
+| 1.0646        | 2.19  | 2500 | 1.1311          |
+| 1.058         | 2.28  | 2600 | 1.1305          |
+| 1.0553        | 2.37  | 2700 | 1.1301          |
+| 1.0607        | 2.45  | 2800 | 1.1298          |
+| 1.0669        | 2.54  | 2900 | 1.1294          |
+| 1.0476        | 2.63  | 3000 | 1.1292          |
+| 1.0688        | 2.72  | 3100 | 1.1291          |
+| 1.0583        | 2.8   | 3200 | 1.1289          |
+| 1.0545        | 2.89  | 3300 | 1.1289          |
+| 1.0744        | 2.98  | 3400 | 1.1289          |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.16.1
+- Tokenizers 0.15.0

all_results.json

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+{
+    "epoch": 3.0,
+    "eval_loss": 1.1288557052612305,
+    "eval_runtime": 427.3581,
+    "eval_samples": 23110,
+    "eval_samples_per_second": 37.828,
+    "eval_steps_per_second": 1.184,
+    "train_loss": 1.2174325642654014,
+    "train_runtime": 53375.7024,
+    "train_samples": 207865,
+    "train_samples_per_second": 8.209,
+    "train_steps_per_second": 0.064
+}

eval_results.json

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+{
+    "epoch": 3.0,
+    "eval_loss": 1.1288557052612305,
+    "eval_runtime": 427.3581,
+    "eval_samples": 23110,
+    "eval_samples_per_second": 37.828,
+    "eval_steps_per_second": 1.184
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.36.2",
+  "use_cache": false
+}

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