metadata
license: apache-2.0
tags:
- token-classification
- generated_from_trainer
datasets:
- ncbi_disease
model-index:
- name: bert-base-cased-finetuned-ner-NCBI_Disease
results: []
bert-base-cased-finetuned-ner-NCBI_Disease
This model is a fine-tuned version of bert-base-cased on the ncbi_disease dataset. It achieves the following results on the evaluation set:
- Loss: 0.0614
- Disease: {'precision': 0.8063891577928364, 'recall': 0.8677083333333333, 'f1': 0.8359257400903161, 'number': 960}
- Overall Precision: 0.8064
- Overall Recall: 0.8677
- Overall F1: 0.8359
- Overall Accuracy: 0.9825
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Disease | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|
| 0.0525 | 1.0 | 340 | 0.0617 | {'precision': 0.7813471502590673, 'recall': 0.7854166666666667, 'f1': 0.7833766233766233, 'number': 960} | 0.7813 | 0.7854 | 0.7834 | 0.9796 |
| 0.022 | 2.0 | 680 | 0.0551 | {'precision': 0.7897240723120837, 'recall': 0.8645833333333334, 'f1': 0.8254599701640976, 'number': 960} | 0.7897 | 0.8646 | 0.8255 | 0.9819 |
| 0.0154 | 3.0 | 1020 | 0.0614 | {'precision': 0.8063891577928364, 'recall': 0.8677083333333333, 'f1': 0.8359257400903161, 'number': 960} | 0.8064 | 0.8677 | 0.8359 | 0.9825 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.13.3