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nominal-groups-recognition-bert-base-spanish-wwm-uncased
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-uncased on the ALazcanoG/spanish_nominal_groups_conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2519
- Body Part Precision: 0.6984
- Body Part Recall: 0.7711
- Body Part F1: 0.7329
- Body Part Number: 1066
- Disease Precision: 0.7230
- Disease Recall: 0.7923
- Disease F1: 0.7561
- Disease Number: 2725
- Family Member Precision: 0.9592
- Family Member Recall: 0.8246
- Family Member F1: 0.8868
- Family Member Number: 57
- Medication Precision: 0.7593
- Medication Recall: 0.7625
- Medication F1: 0.7609
- Medication Number: 240
- Procedure Precision: 0.5439
- Procedure Recall: 0.6389
- Procedure F1: 0.5876
- Procedure Number: 853
- Overall Precision: 0.6885
- Overall Recall: 0.7602
- Overall F1: 0.7226
- Overall Accuracy: 0.9230
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: 2
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4144 | 1.0 | 703 | 0.2530 | 0.6907 | 0.6998 | 0.6952 | 1066 | 0.7309 | 0.7394 | 0.7351 | 2725 | 0.9565 | 0.7719 | 0.8544 | 57 | 0.7798 | 0.7083 | 0.7424 | 240 | 0.5502 | 0.5651 | 0.5575 | 853 | 0.6946 | 0.6997 | 0.6971 | 0.9199 |
| 0.2118 | 2.0 | 1406 | 0.2519 | 0.6984 | 0.7711 | 0.7329 | 1066 | 0.7230 | 0.7923 | 0.7561 | 2725 | 0.9592 | 0.8246 | 0.8868 | 57 | 0.7593 | 0.7625 | 0.7609 | 240 | 0.5439 | 0.6389 | 0.5876 | 853 | 0.6885 | 0.7602 | 0.7226 | 0.9230 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
