End of training
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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: unsloth/Qwen2-1.5B-Instruct
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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: 2633c5c4-0396-4f8a-a5ec-df27508e79f2
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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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# 2633c5c4-0396-4f8a-a5ec-df27508e79f2
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This model is a fine-tuned version of [unsloth/Qwen2-1.5B-Instruct](https://huggingface.co/unsloth/Qwen2-1.5B-Instruct) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0544
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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: 0.000206
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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 | 0.0008 | 1 | 1.1879 |
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| 1.0481 | 0.0410 | 50 | 1.1445 |
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| 1.0289 | 0.0821 | 100 | 1.1724 |
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| 1.0706 | 0.1231 | 150 | 1.1269 |
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| 0.9754 | 0.1641 | 200 | 1.1136 |
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| 1.1411 | 0.2052 | 250 | 1.0916 |
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| 1.0608 | 0.2462 | 300 | 1.0737 |
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| 1.0404 | 0.2872 | 350 | 1.0615 |
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| 0.9828 | 0.3283 | 400 | 1.0560 |
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| 0.9821 | 0.3693 | 450 | 1.0554 |
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| 1.0891 | 0.4103 | 500 | 1.0544 |
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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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