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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: Qwen/Qwen2.5-7B
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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: 65d5a49c-131a-4264-bdee-0528e6e3269d
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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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# 65d5a49c-131a-4264-bdee-0528e6e3269d
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This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5064
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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 | 0.0009 | 1 | 1.9540 |
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| 1.4327 | 0.0430 | 50 | 1.7293 |
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| 1.4125 | 0.0859 | 100 | 1.7308 |
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| 1.4084 | 0.1289 | 150 | 1.7576 |
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| 1.3948 | 0.1718 | 200 | 1.6833 |
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| 1.4067 | 0.2148 | 250 | 1.6334 |
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| 1.479 | 0.2577 | 300 | 1.5825 |
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| 1.447 | 0.3007 | 350 | 1.5370 |
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| 1.1546 | 0.3436 | 400 | 1.5104 |
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| 1.2333 | 0.3866 | 450 | 1.5094 |
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| 1.3885 | 0.4296 | 500 | 1.5064 |
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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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