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nominal-groups-recognition-medical-disease-competencia2-bert-medical-ner

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+ ---
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+ license: openrail
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: nominal-groups-recognition-medical-disease-competencia2-bert-medical-ner
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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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+ # nominal-groups-recognition-medical-disease-competencia2-bert-medical-ner
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+
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+ This model is a fine-tuned version of [ukkendane/bert-medical-ner](https://huggingface.co/ukkendane/bert-medical-ner) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3607
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+ - Body Part Precision: 0.6555
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+ - Body Part Recall: 0.7094
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+ - Body Part F1: 0.6814
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+ - Body Part Number: 413
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+ - Disease Precision: 0.6835
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+ - Disease Recall: 0.7067
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+ - Disease F1: 0.6949
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+ - Disease Number: 975
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+ - Family Member Precision: 1.0
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+ - Family Member Recall: 0.6
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+ - Family Member F1: 0.7500
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+ - Family Member Number: 30
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+ - Medication Precision: 0.7647
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+ - Medication Recall: 0.6989
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+ - Medication F1: 0.7303
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+ - Medication Number: 93
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+ - Procedure Precision: 0.5385
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+ - Procedure Recall: 0.5402
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+ - Procedure F1: 0.5393
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+ - Procedure Number: 311
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+ - Overall Precision: 0.6594
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+ - Overall Recall: 0.6767
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+ - Overall F1: 0.6679
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+ - Overall Accuracy: 0.9079
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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: 13
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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: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Body Part Precision | Body Part Recall | Body Part F1 | Body Part Number | Disease Precision | Disease Recall | Disease F1 | Disease Number | Family Member Precision | Family Member Recall | Family Member F1 | Family Member Number | Medication Precision | Medication Recall | Medication F1 | Medication Number | Procedure Precision | Procedure Recall | Procedure F1 | Procedure Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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+ | 0.4541 | 1.0 | 8025 | 0.3607 | 0.6555 | 0.7094 | 0.6814 | 413 | 0.6835 | 0.7067 | 0.6949 | 975 | 1.0 | 0.6 | 0.7500 | 30 | 0.7647 | 0.6989 | 0.7303 | 93 | 0.5385 | 0.5402 | 0.5393 | 311 | 0.6594 | 0.6767 | 0.6679 | 0.9079 |
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+ | 0.3149 | 2.0 | 16050 | 0.3607 | 0.6555 | 0.7094 | 0.6814 | 413 | 0.6835 | 0.7067 | 0.6949 | 975 | 1.0 | 0.6 | 0.7500 | 30 | 0.7647 | 0.6989 | 0.7303 | 93 | 0.5385 | 0.5402 | 0.5393 | 311 | 0.6594 | 0.6767 | 0.6679 | 0.9079 |
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+ | 0.3161 | 3.0 | 24075 | 0.3607 | 0.6555 | 0.7094 | 0.6814 | 413 | 0.6835 | 0.7067 | 0.6949 | 975 | 1.0 | 0.6 | 0.7500 | 30 | 0.7647 | 0.6989 | 0.7303 | 93 | 0.5385 | 0.5402 | 0.5393 | 311 | 0.6594 | 0.6767 | 0.6679 | 0.9079 |
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+ | 0.3181 | 4.0 | 32100 | 0.3607 | 0.6555 | 0.7094 | 0.6814 | 413 | 0.6835 | 0.7067 | 0.6949 | 975 | 1.0 | 0.6 | 0.7500 | 30 | 0.7647 | 0.6989 | 0.7303 | 93 | 0.5385 | 0.5402 | 0.5393 | 311 | 0.6594 | 0.6767 | 0.6679 | 0.9079 |
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+ | 0.3164 | 5.0 | 40125 | 0.3607 | 0.6555 | 0.7094 | 0.6814 | 413 | 0.6835 | 0.7067 | 0.6949 | 975 | 1.0 | 0.6 | 0.7500 | 30 | 0.7647 | 0.6989 | 0.7303 | 93 | 0.5385 | 0.5402 | 0.5393 | 311 | 0.6594 | 0.6767 | 0.6679 | 0.9079 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.30.2
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.13.1
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+ - Tokenizers 0.13.3