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nominal-groups-recognition-bert-base-spanish-wwm-cased
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the bastianchinchon/spanish_nominal_groups_conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2836
- Body Part Precision: 0.675
- Body Part Recall: 0.7191
- Body Part F1: 0.6964
- Body Part Number: 413
- Disease Precision: 0.7177
- Disease Recall: 0.7405
- Disease F1: 0.7289
- Disease Number: 975
- Family Member Precision: 0.8276
- Family Member Recall: 0.8
- Family Member F1: 0.8136
- Family Member Number: 30
- Medication Precision: 0.8228
- Medication Recall: 0.6989
- Medication F1: 0.7558
- Medication Number: 93
- Procedure Precision: 0.5586
- Procedure Recall: 0.5820
- Procedure F1: 0.5701
- Procedure Number: 311
- Overall Precision: 0.6864
- Overall Recall: 0.7075
- Overall F1: 0.6968
- Overall Accuracy: 0.9146
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4304 | 1.0 | 1004 | 0.2985 | 0.5620 | 0.7022 | 0.6243 | 413 | 0.7059 | 0.6944 | 0.7001 | 975 | 0.8276 | 0.8 | 0.8136 | 30 | 0.6848 | 0.6774 | 0.6811 | 93 | 0.5390 | 0.5113 | 0.5248 | 311 | 0.6415 | 0.6658 | 0.6534 | 0.9028 |
| 0.2346 | 2.0 | 2008 | 0.2836 | 0.675 | 0.7191 | 0.6964 | 413 | 0.7177 | 0.7405 | 0.7289 | 975 | 0.8276 | 0.8 | 0.8136 | 30 | 0.8228 | 0.6989 | 0.7558 | 93 | 0.5586 | 0.5820 | 0.5701 | 311 | 0.6864 | 0.7075 | 0.6968 | 0.9146 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
