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README.md
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---
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library_name: peft
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license: other
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base_model: Qwen/Qwen2.5-3B
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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: 5ecc71a8-d301-438e-b591-988a613c4f15
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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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# 5ecc71a8-d301-438e-b591-988a613c4f15
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This model is a fine-tuned version of [Qwen/Qwen2.5-3B](https://huggingface.co/Qwen/Qwen2.5-3B) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0072
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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: 0.000201
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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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 | 1.2122 |
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| 1.5374 | 0.0042 | 50 | 1.0957 |
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| 1.6613 | 0.0085 | 100 | 1.0716 |
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| 1.5282 | 0.0127 | 150 | 1.0652 |
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| 1.6984 | 0.0170 | 200 | 1.0494 |
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| 1.7164 | 0.0212 | 250 | 1.0364 |
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| 1.3901 | 0.0255 | 300 | 1.0229 |
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| 1.6049 | 0.0297 | 350 | 1.0182 |
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| 1.5117 | 0.0340 | 400 | 1.0120 |
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| 1.4325 | 0.0382 | 450 | 1.0085 |
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| 1.6073 | 0.0425 | 500 | 1.0072 |
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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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