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--- |
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library_name: transformers |
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license: other |
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base_model: Qwen/Qwen1.5-1.8B |
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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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- f1 |
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model-index: |
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- name: gating_network_qwen_1.5 |
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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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# gating_network_qwen_1.5 |
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This model is a fine-tuned version of [Qwen/Qwen1.5-1.8B](https://huggingface.co/Qwen/Qwen1.5-1.8B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0545 |
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- Accuracy: 0.9883 |
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- F1: 0.9876 |
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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: 5e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
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| 0.311 | 0.0252 | 500 | 0.2788 | 0.9236 | 0.9216 | |
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| 0.2235 | 0.0503 | 1000 | 0.1763 | 0.9604 | 0.9591 | |
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| 0.1546 | 0.0755 | 1500 | 0.1805 | 0.9694 | 0.9692 | |
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| 0.1278 | 0.1006 | 2000 | 0.1261 | 0.9784 | 0.9779 | |
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| 0.0893 | 0.1258 | 2500 | 0.1286 | 0.9784 | 0.9788 | |
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| 0.0652 | 0.1510 | 3000 | 0.1357 | 0.9793 | 0.9787 | |
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| 0.0706 | 0.1761 | 3500 | 0.0899 | 0.9865 | 0.9864 | |
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| 0.0551 | 0.2013 | 4000 | 0.1000 | 0.9856 | 0.9849 | |
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| 0.0508 | 0.2264 | 4500 | 0.0662 | 0.9865 | 0.9859 | |
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| 0.0757 | 0.2516 | 5000 | 0.0883 | 0.9847 | 0.9840 | |
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| 0.0611 | 0.2768 | 5500 | 0.1417 | 0.9802 | 0.9797 | |
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| 0.0432 | 0.3019 | 6000 | 0.0545 | 0.9883 | 0.9876 | |
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| 0.0459 | 0.3271 | 6500 | 0.0732 | 0.9874 | 0.9870 | |
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| 0.0597 | 0.3522 | 7000 | 0.0711 | 0.9883 | 0.9883 | |
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| 0.0367 | 0.3774 | 7500 | 0.0742 | 0.9883 | 0.9884 | |
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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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