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--- |
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license: mit |
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base_model: xlm-roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: xlmroberta-finetuned-sem_eval-rest14-english |
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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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# xlmroberta-finetuned-sem_eval-rest14-english |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0880 |
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- F1: 0.4875 |
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- Roc Auc: 0.8755 |
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- Accuracy: 0.7087 |
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- Hamming Loss: 0.0254 |
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | Hamming Loss | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:------------:| |
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| No log | 1.0 | 381 | 0.1858 | 0.0351 | 0.6366 | 0.2288 | 0.0609 | |
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| 0.2234 | 2.0 | 762 | 0.1354 | 0.1345 | 0.6905 | 0.3325 | 0.0418 | |
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| 0.1455 | 3.0 | 1143 | 0.1091 | 0.2639 | 0.7709 | 0.5138 | 0.0343 | |
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| 0.1064 | 4.0 | 1524 | 0.0971 | 0.3768 | 0.8313 | 0.6212 | 0.0282 | |
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| 0.1064 | 5.0 | 1905 | 0.0917 | 0.3767 | 0.8316 | 0.6312 | 0.0286 | |
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| 0.0807 | 6.0 | 2286 | 0.0880 | 0.3966 | 0.8459 | 0.65 | 0.0274 | |
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| 0.0657 | 7.0 | 2667 | 0.0922 | 0.3977 | 0.8513 | 0.6525 | 0.0283 | |
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| 0.0527 | 8.0 | 3048 | 0.0903 | 0.4129 | 0.8555 | 0.6575 | 0.028 | |
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| 0.0527 | 9.0 | 3429 | 0.0921 | 0.4298 | 0.8611 | 0.6713 | 0.0278 | |
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| 0.0453 | 10.0 | 3810 | 0.0882 | 0.4612 | 0.8697 | 0.6887 | 0.0261 | |
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| 0.0385 | 11.0 | 4191 | 0.0859 | 0.4567 | 0.8701 | 0.6925 | 0.0253 | |
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| 0.0339 | 12.0 | 4572 | 0.0881 | 0.4600 | 0.8726 | 0.7025 | 0.0258 | |
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| 0.0339 | 13.0 | 4953 | 0.0882 | 0.4818 | 0.8775 | 0.7063 | 0.0252 | |
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| 0.0304 | 14.0 | 5334 | 0.0879 | 0.4793 | 0.8742 | 0.7 | 0.0254 | |
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| 0.0271 | 15.0 | 5715 | 0.0880 | 0.4875 | 0.8755 | 0.7087 | 0.0254 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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