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README.md
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---
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library_name: peft
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license: apache-2.0
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base_model: NousResearch/Hermes-2-Pro-Mistral-7B
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tags:
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- axolotl
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- generated_from_trainer
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model-index:
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- name: 7ec2af3a-3dbe-4609-af62-5c998569b3e5
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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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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<br>
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# 7ec2af3a-3dbe-4609-af62-5c998569b3e5
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This model is a fine-tuned version of [NousResearch/Hermes-2-Pro-Mistral-7B](https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2782
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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: 0.000218
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 180
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 50
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- training_steps: 500
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| No log | 0.0001 | 1 | 1.8562 |
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| 5.3687 | 0.0068 | 50 | 8.7575 |
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| 5.5762 | 0.0137 | 100 | 2.5470 |
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| 5.2399 | 0.0205 | 150 | 5.4407 |
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| 5.2245 | 0.0273 | 200 | 2.1176 |
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| 4.9681 | 0.0342 | 250 | 2.4473 |
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| 5.4547 | 0.0410 | 300 | 1.5749 |
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| 4.5725 | 0.0478 | 350 | 1.3494 |
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| 5.6604 | 0.0546 | 400 | 1.2976 |
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| 5.0179 | 0.0615 | 450 | 1.2826 |
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| 4.9246 | 0.0683 | 500 | 1.2782 |
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### Framework versions
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- PEFT 0.13.2
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- Transformers 4.46.0
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- Pytorch 2.5.0+cu124
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- Datasets 3.0.1
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- Tokenizers 0.20.1
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