metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: training-1
results: []
training-1
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: 0.0188
- Accuracy: 0.9957
- Precision: 0.9979
- Recall: 0.9936
- F1: 0.9957
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: 1e-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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 0.99 | 175 | 0.0323 | 0.9925 | 1.0 | 0.9850 | 0.9925 |
| 0.1307 | 1.99 | 350 | 0.0291 | 0.9936 | 1.0 | 0.9872 | 0.9935 |
| 0.0299 | 2.98 | 525 | 0.0201 | 0.9957 | 0.9979 | 0.9936 | 0.9957 |
| 0.024 | 3.98 | 700 | 0.0188 | 0.9957 | 0.9979 | 0.9936 | 0.9957 |
| 0.0183 | 4.97 | 875 | 0.0188 | 0.9957 | 0.9979 | 0.9936 | 0.9957 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.2.0.dev20230913+cu121
- Tokenizers 0.13.3