metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: training-8
results: []
training-8
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: 0.0308
- Accuracy: 0.995
- Precision: 0.9955
- Recall: 0.9844
- F1: 0.9899
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 | 262 | 0.0687 | 0.9872 | 0.9755 | 0.9733 | 0.9744 |
| No log | 1.0 | 524 | 0.0501 | 0.9906 | 0.9977 | 0.9644 | 0.9808 |
| 0.1015 | 1.5 | 786 | 0.0465 | 0.9928 | 0.9955 | 0.9756 | 0.9854 |
| 0.1015 | 2.0 | 1048 | 0.0440 | 0.9906 | 0.9932 | 0.9689 | 0.9809 |
| 0.0372 | 2.5 | 1310 | 0.0399 | 0.9922 | 0.9955 | 0.9733 | 0.9843 |
| 0.0372 | 2.99 | 1572 | 0.0298 | 0.995 | 0.9955 | 0.9844 | 0.9899 |
| 0.0131 | 3.49 | 1834 | 0.0312 | 0.995 | 0.9955 | 0.9844 | 0.9899 |
| 0.0131 | 3.99 | 2096 | 0.0308 | 0.995 | 0.9955 | 0.9844 | 0.9899 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.2.0.dev20230913+cu121
- Tokenizers 0.13.3