metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: text-classification-medical
results: []
text-classification-medical
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0394
- Accuracy: 1.0
- F1: 1.0
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 13 | 0.6409 | 0.5714 | 0.7273 |
| No log | 2.0 | 26 | 0.5385 | 0.8297 | 0.8397 |
| No log | 3.0 | 39 | 0.3346 | 0.9286 | 0.9293 |
| No log | 4.0 | 52 | 0.1979 | 0.9780 | 0.9781 |
| No log | 5.0 | 65 | 0.1321 | 0.9945 | 0.9945 |
| No log | 6.0 | 78 | 0.0932 | 1.0 | 1.0 |
| No log | 7.0 | 91 | 0.0654 | 1.0 | 1.0 |
| No log | 8.0 | 104 | 0.0508 | 1.0 | 1.0 |
| No log | 9.0 | 117 | 0.0420 | 1.0 | 1.0 |
| No log | 10.0 | 130 | 0.0394 | 1.0 | 1.0 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0