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--- |
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license: apache-2.0 |
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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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- unsloth |
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- generated_from_trainer |
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base_model: unsloth/llama-3-8b-Instruct-bnb-4bit |
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model-index: |
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- name: llama3-chat_10000_500 |
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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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# llama3-chat_10000_500 |
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This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct-bnb-4bit](https://huggingface.co/unsloth/llama-3-8b-Instruct-bnb-4bit) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8491 |
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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: 4 |
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- seed: 3407 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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_steps: 5 |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.765 | 0.33 | 104 | 1.4841 | |
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| 1.5146 | 0.67 | 208 | 1.4604 | |
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| 1.4912 | 1.0 | 312 | 1.4545 | |
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| 1.3584 | 1.33 | 416 | 1.4698 | |
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| 1.358 | 1.66 | 520 | 1.4671 | |
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| 1.3483 | 2.0 | 624 | 1.4637 | |
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| 1.1105 | 2.33 | 728 | 1.5471 | |
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| 1.101 | 2.66 | 832 | 1.5512 | |
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| 1.1007 | 3.0 | 936 | 1.5522 | |
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| 0.8526 | 3.33 | 1040 | 1.7081 | |
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| 0.8445 | 3.66 | 1144 | 1.7156 | |
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| 0.8463 | 3.99 | 1248 | 1.7115 | |
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| 0.6865 | 4.33 | 1352 | 1.8423 | |
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| 0.6811 | 4.66 | 1456 | 1.8458 | |
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| 0.6859 | 4.99 | 1560 | 1.8491 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.39.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.2 |
