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nercomlower-bert-base-spanish-wwm-cased
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the simonestradasch/NERcomp2lower dataset. It achieves the following results on the evaluation set:
- Loss: 0.2448
- Body Part Precision: 0.7140
- Body Part Recall: 0.7676
- Body Part F1: 0.7398
- Body Part Number: 413
- Disease Precision: 0.7505
- Disease Recall: 0.7805
- Disease F1: 0.7652
- Disease Number: 975
- Family Member Precision: 0.875
- Family Member Recall: 0.9333
- Family Member F1: 0.9032
- Family Member Number: 30
- Medication Precision: 0.8764
- Medication Recall: 0.8387
- Medication F1: 0.8571
- Medication Number: 93
- Procedure Precision: 0.6571
- Procedure Recall: 0.6656
- Procedure F1: 0.6613
- Procedure Number: 311
- Overall Precision: 0.7344
- Overall Recall: 0.7634
- Overall F1: 0.7487
- Overall Accuracy: 0.9277
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.355 | 1.0 | 1004 | 0.2520 | 0.7073 | 0.8015 | 0.7514 | 413 | 0.7485 | 0.7477 | 0.7481 | 975 | 0.8710 | 0.9 | 0.8852 | 30 | 0.7196 | 0.8280 | 0.77 | 93 | 0.5804 | 0.6270 | 0.6028 | 311 | 0.7093 | 0.7459 | 0.7271 | 0.9219 |
| 0.1869 | 2.0 | 2008 | 0.2448 | 0.7140 | 0.7676 | 0.7398 | 413 | 0.7505 | 0.7805 | 0.7652 | 975 | 0.875 | 0.9333 | 0.9032 | 30 | 0.8764 | 0.8387 | 0.8571 | 93 | 0.6571 | 0.6656 | 0.6613 | 311 | 0.7344 | 0.7634 | 0.7487 | 0.9277 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
