metadata
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_large_with_preprocessing_grid_search
results: []
BERT_large_with_preprocessing_grid_search
This model is a fine-tuned version of bert-large-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.0732
- Precision: 0.0194
- Recall: 0.125
- F1: 0.0336
- Accuracy: 0.1551
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 |
|---|---|---|---|---|---|---|---|
| 2.1235 | 1.0 | 510 | 2.0738 | 0.0284 | 0.125 | 0.0462 | 0.2268 |
| 2.1058 | 2.0 | 1020 | 2.0805 | 0.0194 | 0.125 | 0.0336 | 0.1551 |
| 2.1039 | 3.0 | 1530 | 2.0780 | 0.0345 | 0.125 | 0.0541 | 0.2759 |
| 2.1045 | 4.0 | 2040 | 2.0734 | 0.0284 | 0.125 | 0.0462 | 0.2268 |
| 2.0963 | 5.0 | 2550 | 2.0779 | 0.0041 | 0.125 | 0.0080 | 0.0329 |
| 2.0975 | 6.0 | 3060 | 2.0750 | 0.0284 | 0.125 | 0.0462 | 0.2268 |
| 2.0944 | 7.0 | 3570 | 2.0734 | 0.0194 | 0.125 | 0.0336 | 0.1551 |
| 2.1004 | 8.0 | 4080 | 2.0820 | 0.0029 | 0.125 | 0.0056 | 0.0231 |
| 2.0974 | 9.0 | 4590 | 2.0724 | 0.0187 | 0.125 | 0.0326 | 0.1497 |
| 2.0936 | 10.0 | 5100 | 2.0732 | 0.0194 | 0.125 | 0.0336 | 0.1551 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3