metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: training-6
results: []
training-6
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0431
- Accuracy: 0.9923
- Precision: 0.9942
- Recall: 0.9752
- F1: 0.9846
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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 0.5 | 302 | 0.0633 | 0.9894 | 0.9980 | 0.9599 | 0.9786 |
| No log | 1.0 | 604 | 0.0501 | 0.9846 | 0.9713 | 0.9676 | 0.9694 |
| 0.0875 | 1.5 | 906 | 0.0621 | 0.9899 | 0.9980 | 0.9618 | 0.9796 |
| 0.0875 | 2.0 | 1208 | 0.0420 | 0.9928 | 0.9961 | 0.9752 | 0.9855 |
| 0.0269 | 2.5 | 1510 | 0.0509 | 0.9923 | 0.9980 | 0.9714 | 0.9845 |
| 0.0269 | 3.0 | 1812 | 0.0456 | 0.9932 | 1.0 | 0.9733 | 0.9865 |
| 0.0159 | 3.49 | 2114 | 0.0452 | 0.9937 | 1.0 | 0.9752 | 0.9874 |
| 0.0159 | 3.99 | 2416 | 0.0431 | 0.9923 | 0.9942 | 0.9752 | 0.9846 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.2.0.dev20230913+cu121
- Tokenizers 0.13.3