metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-medical-ner
results: []
bert-medical-ner
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3752
- Precision: 0.7403
- Recall: 0.6800
- F1: 0.7089
- Accuracy: 0.9401
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 63 | 0.3364 | 0.6802 | 0.6433 | 0.6612 | 0.9325 |
| No log | 2.0 | 126 | 0.3434 | 0.6759 | 0.6789 | 0.6774 | 0.9331 |
| No log | 3.0 | 189 | 0.3381 | 0.7297 | 0.6851 | 0.7067 | 0.9389 |
| No log | 4.0 | 252 | 0.3470 | 0.6788 | 0.6942 | 0.6864 | 0.9333 |
| No log | 5.0 | 315 | 0.3668 | 0.7392 | 0.6761 | 0.7062 | 0.9380 |
| No log | 6.0 | 378 | 0.3722 | 0.7565 | 0.6710 | 0.7112 | 0.9416 |
| No log | 7.0 | 441 | 0.3669 | 0.7253 | 0.6806 | 0.7022 | 0.9386 |
| 0.0633 | 8.0 | 504 | 0.3673 | 0.7250 | 0.6914 | 0.7078 | 0.9404 |
| 0.0633 | 9.0 | 567 | 0.3789 | 0.7456 | 0.6744 | 0.7082 | 0.9405 |
| 0.0633 | 10.0 | 630 | 0.3752 | 0.7403 | 0.6800 | 0.7089 | 0.9401 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3