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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_rse |
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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_rse |
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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: 0.0243 |
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- Accuracy: 0.9961 |
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- F1: 0.9961 |
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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: 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: 15 |
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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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| 0.8808 | 1.0 | 276 | 0.2620 | 0.9237 | 0.9242 | |
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| 0.3108 | 2.0 | 552 | 0.2273 | 0.9471 | 0.9470 | |
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| 0.2543 | 3.0 | 828 | 0.1193 | 0.9700 | 0.9700 | |
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| 0.1788 | 4.0 | 1104 | 0.1284 | 0.9702 | 0.9705 | |
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| 0.1296 | 5.0 | 1380 | 0.0549 | 0.9891 | 0.9891 | |
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| 0.0669 | 6.0 | 1656 | 0.0398 | 0.9927 | 0.9927 | |
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| 0.0658 | 7.0 | 1932 | 0.0299 | 0.9957 | 0.9957 | |
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| 0.0379 | 8.0 | 2208 | 0.0216 | 0.9964 | 0.9964 | |
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| 0.0312 | 9.0 | 2484 | 0.0243 | 0.9961 | 0.9961 | |
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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 3.3.1 |
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- Tokenizers 0.21.0 |
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