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--- |
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library_name: peft |
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license: gemma |
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base_model: unsloth/gemma-2-2b |
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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: 5a4bf373-7928-4fea-aea6-2b0160f5d1c9 |
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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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# 5a4bf373-7928-4fea-aea6-2b0160f5d1c9 |
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This model is a fine-tuned version of [unsloth/gemma-2-2b](https://huggingface.co/unsloth/gemma-2-2b) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3595 |
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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: 0.00021 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 100 |
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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 | 0.0000 | 1 | 1.6350 | |
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| 1.3774 | 0.0008 | 50 | 1.4623 | |
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| 1.3825 | 0.0017 | 100 | 1.4445 | |
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| 1.3845 | 0.0025 | 150 | 1.4355 | |
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| 1.2979 | 0.0033 | 200 | 1.4278 | |
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| 1.3492 | 0.0041 | 250 | 1.4065 | |
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| 1.2435 | 0.0050 | 300 | 1.3964 | |
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| 1.2813 | 0.0058 | 350 | 1.3751 | |
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| 1.3393 | 0.0066 | 400 | 1.3661 | |
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| 1.3273 | 0.0075 | 450 | 1.3599 | |
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| 1.2704 | 0.0083 | 500 | 1.3595 | |
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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 |
