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update model card README.md

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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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+ model-index:
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+ - name: distemist_NER_test
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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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+ # distemist_NER_test
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+
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+ This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0927
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+ - Diso Precision: 0.7135
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+ - Diso Recall: 0.7799
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+ - Diso F1: 0.7452
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+ - Diso Number: 1440
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+ - Overall Precision: 0.7135
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+ - Overall Recall: 0.7799
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+ - Overall F1: 0.7452
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+ - Overall Accuracy: 0.9760
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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: 4
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-----------------:|:--------------:|:----------:|:----------------:|
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+ | 0.0992 | 1.0 | 1169 | 0.0778 | 0.6166 | 0.7639 | 0.6824 | 1440 | 0.6166 | 0.7639 | 0.6824 | 0.9705 |
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+ | 0.0603 | 2.0 | 2338 | 0.0721 | 0.6867 | 0.7840 | 0.7322 | 1440 | 0.6867 | 0.7840 | 0.7322 | 0.9757 |
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+ | 0.0371 | 3.0 | 3507 | 0.0812 | 0.7182 | 0.7736 | 0.7449 | 1440 | 0.7182 | 0.7736 | 0.7449 | 0.9764 |
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+ | 0.0198 | 4.0 | 4676 | 0.0927 | 0.7135 | 0.7799 | 0.7452 | 1440 | 0.7135 | 0.7799 | 0.7452 | 0.9760 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 1.13.1+cu116
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+ - Datasets 2.10.0
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+ - Tokenizers 0.13.2