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--- |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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library_name: peft |
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license: llama3.1 |
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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: Llama-31-8B_task-1_180-samples_config-4_full |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Llama-31-8B_task-1_180-samples_config-4_full |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3.1-8B-Instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9228 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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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: 0.1 |
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- num_epochs: 150 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 2.4745 | 0.9412 | 8 | 2.4335 | |
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| 2.4286 | 2.0 | 17 | 2.4114 | |
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| 2.419 | 2.9412 | 25 | 2.3814 | |
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| 2.3475 | 4.0 | 34 | 2.3262 | |
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| 2.3147 | 4.9412 | 42 | 2.2541 | |
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| 2.2214 | 6.0 | 51 | 2.1716 | |
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| 2.1097 | 6.9412 | 59 | 2.0745 | |
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| 1.9617 | 8.0 | 68 | 1.9479 | |
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| 1.908 | 8.9412 | 76 | 1.8375 | |
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| 1.7669 | 10.0 | 85 | 1.6953 | |
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| 1.6325 | 10.9412 | 93 | 1.5461 | |
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| 1.3201 | 12.0 | 102 | 1.3739 | |
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| 1.2477 | 12.9412 | 110 | 1.2331 | |
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| 1.163 | 14.0 | 119 | 1.1330 | |
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| 1.0579 | 14.9412 | 127 | 1.0861 | |
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| 1.0655 | 16.0 | 136 | 1.0611 | |
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| 0.9976 | 16.9412 | 144 | 1.0455 | |
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| 1.0285 | 18.0 | 153 | 1.0318 | |
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| 0.998 | 18.9412 | 161 | 1.0205 | |
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| 1.0038 | 20.0 | 170 | 1.0102 | |
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| 0.9907 | 20.9412 | 178 | 1.0020 | |
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| 0.9673 | 22.0 | 187 | 0.9929 | |
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| 0.95 | 22.9412 | 195 | 0.9870 | |
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| 0.9467 | 24.0 | 204 | 0.9801 | |
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| 0.9423 | 24.9412 | 212 | 0.9737 | |
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| 0.937 | 26.0 | 221 | 0.9675 | |
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| 0.9035 | 26.9412 | 229 | 0.9626 | |
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| 0.9074 | 28.0 | 238 | 0.9582 | |
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| 0.8944 | 28.9412 | 246 | 0.9534 | |
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| 0.8785 | 30.0 | 255 | 0.9493 | |
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| 0.8797 | 30.9412 | 263 | 0.9451 | |
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| 0.8764 | 32.0 | 272 | 0.9422 | |
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| 0.8903 | 32.9412 | 280 | 0.9389 | |
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| 0.8835 | 34.0 | 289 | 0.9377 | |
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| 0.8452 | 34.9412 | 297 | 0.9332 | |
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| 0.8777 | 36.0 | 306 | 0.9272 | |
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| 0.8101 | 36.9412 | 314 | 0.9257 | |
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| 0.8526 | 38.0 | 323 | 0.9229 | |
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| 0.8228 | 38.9412 | 331 | 0.9197 | |
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| 0.8066 | 40.0 | 340 | 0.9176 | |
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| 0.7701 | 40.9412 | 348 | 0.9199 | |
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| 0.8132 | 42.0 | 357 | 0.9162 | |
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| 0.7804 | 42.9412 | 365 | 0.9104 | |
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| 0.7508 | 44.0 | 374 | 0.9083 | |
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| 0.7192 | 44.9412 | 382 | 0.9052 | |
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| 0.7633 | 46.0 | 391 | 0.9048 | |
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| 0.7534 | 46.9412 | 399 | 0.9052 | |
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| 0.666 | 48.0 | 408 | 0.9151 | |
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| 0.7298 | 48.9412 | 416 | 0.9143 | |
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| 0.6815 | 50.0 | 425 | 0.9157 | |
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| 0.6845 | 50.9412 | 433 | 0.9170 | |
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| 0.6524 | 52.0 | 442 | 0.9216 | |
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| 0.6397 | 52.9412 | 450 | 0.9228 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
