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--- |
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license: llama3 |
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library_name: peft |
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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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base_model: meta-llama/Meta-Llama-3-8B-Instruct |
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model-index: |
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- name: unaligned |
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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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# unaligned |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0709 |
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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: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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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: linear |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 2048 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.1154 | 0.1110 | 100 | 0.1172 | |
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| 0.092 | 0.2220 | 200 | 0.1028 | |
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| 0.0462 | 0.3330 | 300 | 0.0992 | |
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| 0.0482 | 0.4440 | 400 | 0.0755 | |
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| 0.043 | 0.5550 | 500 | 0.0794 | |
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| 0.0476 | 0.6660 | 600 | 0.0628 | |
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| 0.0482 | 0.7770 | 700 | 0.0821 | |
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| 0.0484 | 0.8880 | 800 | 0.0691 | |
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| 0.0448 | 0.9990 | 900 | 0.0829 | |
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| 0.0214 | 1.1100 | 1000 | 0.0720 | |
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| 0.0439 | 1.2210 | 1100 | 0.0635 | |
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| 0.0364 | 1.3320 | 1200 | 0.0713 | |
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| 0.0497 | 1.4430 | 1300 | 0.0669 | |
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| 0.0455 | 1.5540 | 1400 | 0.0672 | |
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| 0.0614 | 1.6650 | 1500 | 0.0805 | |
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| 0.0416 | 1.7761 | 1600 | 0.0669 | |
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| 0.0367 | 1.8871 | 1700 | 0.0716 | |
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| 0.0578 | 1.9981 | 1800 | 0.0684 | |
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| 0.0358 | 2.1091 | 1900 | 0.0705 | |
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| 0.0326 | 2.2201 | 2000 | 0.0709 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
