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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-v0.1 |
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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 [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2423 |
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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: 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: 10 |
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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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| 1.5123 | 0.01 | 1 | 1.5038 | |
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| 1.3662 | 0.06 | 5 | 1.4103 | |
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| 1.1836 | 0.11 | 10 | 1.3055 | |
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| 1.2761 | 0.17 | 15 | 1.2810 | |
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| 1.1779 | 0.22 | 20 | 1.2696 | |
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| 1.1242 | 0.28 | 25 | 1.2642 | |
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| 1.2414 | 0.33 | 30 | 1.2588 | |
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| 1.1382 | 0.39 | 35 | 1.2555 | |
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| 1.2094 | 0.45 | 40 | 1.2520 | |
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| 1.1049 | 0.5 | 45 | 1.2504 | |
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| 1.1709 | 0.56 | 50 | 1.2487 | |
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| 1.0981 | 0.61 | 55 | 1.2463 | |
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| 1.1902 | 0.67 | 60 | 1.2446 | |
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| 1.1526 | 0.72 | 65 | 1.2446 | |
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| 1.1319 | 0.78 | 70 | 1.2440 | |
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| 1.1913 | 0.84 | 75 | 1.2430 | |
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| 1.1875 | 0.89 | 80 | 1.2424 | |
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| 1.1454 | 0.95 | 85 | 1.2423 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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