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README.md ADDED
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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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+
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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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+
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+ # xlmroberta-finetuned-sem_eval-rest14-english
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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