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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: Qwen/Qwen2-1.5B |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: fine_tuned_yelp_callback10 |
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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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# fine_tuned_yelp_callback10 |
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This model is a fine-tuned version of [Qwen/Qwen2-1.5B](https://huggingface.co/Qwen/Qwen2-1.5B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2174 |
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- Accuracy: 0.9601 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 0.8575 | 0.0170 | 100 | 0.4890 | 0.8281 | |
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| 0.7118 | 0.0340 | 200 | 0.5564 | 0.8484 | |
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| 0.5044 | 0.0509 | 300 | 0.5218 | 0.8463 | |
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| 0.3969 | 0.0679 | 400 | 0.9168 | 0.7809 | |
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| 0.4494 | 0.0849 | 500 | 0.5158 | 0.8453 | |
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| 0.3766 | 0.1019 | 600 | 0.5252 | 0.8772 | |
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| 0.3938 | 0.1188 | 700 | 0.5676 | 0.8573 | |
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| 0.3681 | 0.1358 | 800 | 0.2930 | 0.9116 | |
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| 0.3955 | 0.1528 | 900 | 0.2745 | 0.8845 | |
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| 0.2859 | 0.1698 | 1000 | 0.3442 | 0.9150 | |
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| 0.329 | 0.1868 | 1100 | 0.2673 | 0.9116 | |
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| 0.2898 | 0.2037 | 1200 | 0.1957 | 0.9221 | |
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| 0.2645 | 0.2207 | 1300 | 0.2623 | 0.9335 | |
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| 0.2906 | 0.2377 | 1400 | 0.2438 | 0.9280 | |
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| 0.2511 | 0.2547 | 1500 | 0.3281 | 0.9211 | |
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| 0.3 | 0.2716 | 1600 | 0.1789 | 0.9467 | |
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| 0.2592 | 0.2886 | 1700 | 0.2963 | 0.9270 | |
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| 0.2274 | 0.3056 | 1800 | 0.3387 | 0.9309 | |
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| 0.2843 | 0.3226 | 1900 | 0.2788 | 0.9291 | |
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| 0.281 | 0.3396 | 2000 | 0.2553 | 0.9442 | |
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| 0.2624 | 0.3565 | 2100 | 0.1737 | 0.9547 | |
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| 0.2503 | 0.3735 | 2200 | 0.1948 | 0.9454 | |
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| 0.2856 | 0.3905 | 2300 | 0.2797 | 0.9269 | |
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| 0.1531 | 0.4075 | 2400 | 0.2548 | 0.9490 | |
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| 0.2316 | 0.4244 | 2500 | 0.2906 | 0.9440 | |
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| 0.2061 | 0.4414 | 2600 | 0.2194 | 0.9517 | |
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| 0.1991 | 0.4584 | 2700 | 0.1949 | 0.9515 | |
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| 0.1721 | 0.4754 | 2800 | 0.2730 | 0.9368 | |
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| 0.1696 | 0.4924 | 2900 | 0.2238 | 0.9326 | |
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| 0.2013 | 0.5093 | 3000 | 0.1802 | 0.9603 | |
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| 0.2026 | 0.5263 | 3100 | 0.2174 | 0.9601 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu126 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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