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--- |
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library_name: transformers |
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license: mit |
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base_model: microsoft/deberta-v3-base |
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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: deberta_Energie |
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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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# deberta_Energie |
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0142 |
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- Accuracy: 0.9913 |
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- F1: 0.9913 |
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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-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: 30 |
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- mixed_precision_training: Native AMP |
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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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| 1.4003 | 1.0 | 116 | 0.9262 | 0.6524 | 0.6025 | |
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| 0.7697 | 2.0 | 232 | 0.3836 | 0.8906 | 0.8899 | |
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| 0.3904 | 3.0 | 348 | 0.2468 | 0.9256 | 0.9191 | |
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| 0.2749 | 4.0 | 464 | 0.2202 | 0.9324 | 0.9283 | |
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| 0.2043 | 5.0 | 580 | 0.1122 | 0.9672 | 0.9673 | |
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| 0.1808 | 6.0 | 696 | 0.1004 | 0.9701 | 0.9706 | |
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| 0.1274 | 7.0 | 812 | 0.0822 | 0.9745 | 0.9747 | |
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| 0.1018 | 8.0 | 928 | 0.0673 | 0.9791 | 0.9794 | |
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| 0.0711 | 9.0 | 1044 | 0.0457 | 0.9870 | 0.9870 | |
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| 0.0609 | 10.0 | 1160 | 0.0370 | 0.9867 | 0.9867 | |
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| 0.0594 | 11.0 | 1276 | 0.0240 | 0.9886 | 0.9886 | |
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| 0.0332 | 12.0 | 1392 | 0.0182 | 0.9913 | 0.9913 | |
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| 0.0278 | 13.0 | 1508 | 0.0183 | 0.9908 | 0.9908 | |
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| 0.0281 | 14.0 | 1624 | 0.0142 | 0.9913 | 0.9913 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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