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nominal-groups-recognition-medical-disease-beto-cmm-competencia2-beto-prescripciones-medicas
This model is a fine-tuned version of ccarvajal/beto-prescripciones-medicas on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4614
- Body Part Precision: 0.3804
- Body Part Recall: 0.4697
- Body Part F1: 0.4204
- Body Part Number: 413
- Disease Precision: 0.4680
- Disease Recall: 0.5477
- Disease F1: 0.5047
- Disease Number: 975
- Family Member Precision: 1.0
- Family Member Recall: 0.6
- Family Member F1: 0.7500
- Family Member Number: 30
- Medication Precision: 0.6364
- Medication Recall: 0.0753
- Medication F1: 0.1346
- Medication Number: 93
- Procedure Precision: 0.4139
- Procedure Recall: 0.3248
- Procedure F1: 0.3640
- Procedure Number: 311
- Overall Precision: 0.4439
- Overall Recall: 0.4687
- Overall F1: 0.4560
- Overall Accuracy: 0.8689
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 13
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.5675 | 1.0 | 8025 | 0.4614 | 0.3804 | 0.4697 | 0.4204 | 413 | 0.4680 | 0.5477 | 0.5047 | 975 | 1.0 | 0.6 | 0.7500 | 30 | 0.6364 | 0.0753 | 0.1346 | 93 | 0.4139 | 0.3248 | 0.3640 | 311 | 0.4439 | 0.4687 | 0.4560 | 0.8689 |
0.4162 | 2.0 | 16050 | 0.4614 | 0.3804 | 0.4697 | 0.4204 | 413 | 0.4680 | 0.5477 | 0.5047 | 975 | 1.0 | 0.6 | 0.7500 | 30 | 0.6364 | 0.0753 | 0.1346 | 93 | 0.4139 | 0.3248 | 0.3640 | 311 | 0.4439 | 0.4687 | 0.4560 | 0.8689 |
0.4146 | 3.0 | 24075 | 0.4614 | 0.3804 | 0.4697 | 0.4204 | 413 | 0.4680 | 0.5477 | 0.5047 | 975 | 1.0 | 0.6 | 0.7500 | 30 | 0.6364 | 0.0753 | 0.1346 | 93 | 0.4139 | 0.3248 | 0.3640 | 311 | 0.4439 | 0.4687 | 0.4560 | 0.8689 |
0.4163 | 4.0 | 32100 | 0.4614 | 0.3804 | 0.4697 | 0.4204 | 413 | 0.4680 | 0.5477 | 0.5047 | 975 | 1.0 | 0.6 | 0.7500 | 30 | 0.6364 | 0.0753 | 0.1346 | 93 | 0.4139 | 0.3248 | 0.3640 | 311 | 0.4439 | 0.4687 | 0.4560 | 0.8689 |
0.4139 | 5.0 | 40125 | 0.4614 | 0.3804 | 0.4697 | 0.4204 | 413 | 0.4680 | 0.5477 | 0.5047 | 975 | 1.0 | 0.6 | 0.7500 | 30 | 0.6364 | 0.0753 | 0.1346 | 93 | 0.4139 | 0.3248 | 0.3640 | 311 | 0.4439 | 0.4687 | 0.4560 | 0.8689 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3