metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_with_preprocessing_grid_search
results: []
BERT_with_preprocessing_grid_search
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: 0.8836
- Precision: 0.8262
- Recall: 0.8258
- F1: 0.8249
- Accuracy: 0.8724
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: 3e-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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.047 | 1.0 | 510 | 0.6171 | 0.7493 | 0.8057 | 0.7716 | 0.8336 |
| 0.4348 | 2.0 | 1020 | 0.4954 | 0.8056 | 0.8646 | 0.8296 | 0.8714 |
| 0.2818 | 3.0 | 1530 | 0.6252 | 0.8181 | 0.8323 | 0.8212 | 0.8660 |
| 0.1793 | 4.0 | 2040 | 0.7381 | 0.8216 | 0.8258 | 0.8227 | 0.8733 |
| 0.1356 | 5.0 | 2550 | 0.8601 | 0.8161 | 0.8219 | 0.8165 | 0.8660 |
| 0.1023 | 6.0 | 3060 | 0.8526 | 0.8363 | 0.8299 | 0.8307 | 0.8758 |
| 0.0944 | 7.0 | 3570 | 0.8459 | 0.8234 | 0.8298 | 0.8251 | 0.8729 |
| 0.0631 | 8.0 | 4080 | 0.8519 | 0.8212 | 0.8325 | 0.8252 | 0.8714 |
| 0.0602 | 9.0 | 4590 | 0.8756 | 0.8200 | 0.8267 | 0.8226 | 0.8719 |
| 0.0532 | 10.0 | 5100 | 0.8836 | 0.8262 | 0.8258 | 0.8249 | 0.8724 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3