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Bio-RoBERTime

Token Classification
Transformers
PyTorch
roberta
LABEL-0 = NONE
LABEL-1 = B-DATE
LABEL-2 = I-DATE
LABEL-3 = B-TIME
LABEL-4 = I-TIME
LABEL-5 = B-DURATION
LABEL-6 = I-DURATION
LABEL-7 = B-SET
LABEL-8 = I-SET
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: Bio-RoBERTime
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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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+ # Bio-RoBERTime
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+
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+ This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-biomedical-clinical-es](https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-clinical-es) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0177
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+ - Precision: 0.8121
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+ - Recall: 0.8854
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+ - F1: 0.8472
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+ - Accuracy: 0.9919
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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: 8e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 72
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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: 24
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0433 | 1.0 | 12 | 0.0443 | 0.4948 | 0.5 | 0.4974 | 0.9800 |
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+ | 0.0234 | 2.0 | 24 | 0.0221 | 0.4082 | 0.7257 | 0.5225 | 0.9732 |
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+ | 0.0055 | 3.0 | 36 | 0.0159 | 0.4768 | 0.7847 | 0.5932 | 0.9797 |
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+ | 0.0089 | 4.0 | 48 | 0.0153 | 0.5317 | 0.8160 | 0.6438 | 0.9813 |
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+ | 0.0033 | 5.0 | 60 | 0.0131 | 0.7229 | 0.8333 | 0.7742 | 0.9896 |
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+ | 0.008 | 6.0 | 72 | 0.0129 | 0.6649 | 0.8681 | 0.7530 | 0.9885 |
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+ | 0.0063 | 7.0 | 84 | 0.0146 | 0.7523 | 0.8542 | 0.8 | 0.9904 |
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+ | 0.0086 | 8.0 | 96 | 0.0150 | 0.7470 | 0.8715 | 0.8045 | 0.9906 |
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+ | 0.0009 | 9.0 | 108 | 0.0139 | 0.7658 | 0.8854 | 0.8213 | 0.9910 |
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+ | 0.0031 | 10.0 | 120 | 0.0159 | 0.8031 | 0.8924 | 0.8454 | 0.9919 |
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+ | 0.0011 | 11.0 | 132 | 0.0158 | 0.7649 | 0.8924 | 0.8237 | 0.9909 |
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+ | 0.0006 | 12.0 | 144 | 0.0153 | 0.7398 | 0.8785 | 0.8032 | 0.9902 |
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+ | 0.0013 | 13.0 | 156 | 0.0157 | 0.7815 | 0.8819 | 0.8287 | 0.9910 |
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+ | 0.0008 | 14.0 | 168 | 0.0154 | 0.7822 | 0.8854 | 0.8306 | 0.9908 |
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+ | 0.0008 | 15.0 | 180 | 0.0164 | 0.7778 | 0.875 | 0.8235 | 0.9910 |
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+ | 0.0007 | 16.0 | 192 | 0.0168 | 0.7864 | 0.8819 | 0.8314 | 0.9912 |
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+ | 0.0018 | 17.0 | 204 | 0.0173 | 0.7870 | 0.8854 | 0.8333 | 0.9912 |
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+ | 0.0006 | 18.0 | 216 | 0.0178 | 0.7730 | 0.875 | 0.8208 | 0.9914 |
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+ | 0.0012 | 19.0 | 228 | 0.0171 | 0.8013 | 0.8819 | 0.8397 | 0.9916 |
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+ | 0.0006 | 20.0 | 240 | 0.0181 | 0.8137 | 0.8646 | 0.8384 | 0.9916 |
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+ | 0.0007 | 21.0 | 252 | 0.0186 | 0.8137 | 0.8646 | 0.8384 | 0.9918 |
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+ | 0.0012 | 22.0 | 264 | 0.0188 | 0.8137 | 0.8646 | 0.8384 | 0.9919 |
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+ | 0.0006 | 23.0 | 276 | 0.0178 | 0.8121 | 0.8854 | 0.8472 | 0.9919 |
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+ | 0.0009 | 24.0 | 288 | 0.0177 | 0.8121 | 0.8854 | 0.8472 | 0.9919 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.24.0
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 2.7.0
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+ - Tokenizers 0.13.2