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--- |
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base_model: meta-llama/Llama-2-13b-hf |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: qlora-out |
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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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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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# qlora-out |
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This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5407 |
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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: 0.0004 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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: 300 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.8973 | 0.03 | 20 | 0.7029 | |
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| 0.6828 | 0.06 | 40 | 0.6521 | |
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| 0.6521 | 0.09 | 60 | 0.6199 | |
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| 0.7857 | 0.11 | 80 | 0.6066 | |
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| 0.6208 | 0.14 | 100 | 0.6063 | |
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| 0.6805 | 0.17 | 120 | 0.5969 | |
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| 0.5928 | 0.2 | 140 | 0.5989 | |
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| 0.715 | 0.23 | 160 | 0.5844 | |
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| 0.5647 | 0.26 | 180 | 0.5979 | |
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| 0.6778 | 0.29 | 200 | 0.5889 | |
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| 0.5907 | 0.31 | 220 | 0.5772 | |
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| 0.5536 | 0.34 | 240 | 0.5917 | |
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| 0.7422 | 0.37 | 260 | 0.6781 | |
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| 0.6328 | 0.4 | 280 | 0.5785 | |
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| 0.5705 | 0.43 | 300 | 0.5720 | |
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| 0.6124 | 0.46 | 320 | 0.5753 | |
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| 0.4735 | 0.49 | 340 | 0.6203 | |
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| 0.4602 | 0.52 | 360 | 0.5772 | |
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| 0.8571 | 0.54 | 380 | 0.5750 | |
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| 0.5504 | 0.57 | 400 | 0.6040 | |
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| 0.6307 | 0.6 | 420 | 0.5796 | |
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| 0.4782 | 0.63 | 440 | 0.5639 | |
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| 0.4159 | 0.66 | 460 | 0.5689 | |
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| 0.6393 | 0.69 | 480 | 0.5661 | |
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| 0.8243 | 0.72 | 500 | 0.5698 | |
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| 0.4744 | 0.74 | 520 | 0.5536 | |
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| 0.4395 | 0.77 | 540 | 0.5536 | |
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| 0.543 | 0.8 | 560 | 0.5493 | |
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| 0.4451 | 0.83 | 580 | 0.5421 | |
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| 0.5384 | 0.86 | 600 | 0.5467 | |
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| 0.4438 | 0.89 | 620 | 0.5379 | |
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| 0.4168 | 0.92 | 640 | 0.5398 | |
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| 0.469 | 0.94 | 660 | 0.5402 | |
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| 0.6766 | 0.97 | 680 | 0.5407 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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