metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-detests
results: []
bert-base-uncased-finetuned-detests
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: 1.0660
- Accuracy: 0.8232
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: 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 | Accuracy |
|---|---|---|---|---|
| 0.4677 | 1.0 | 153 | 0.4412 | 0.8101 |
| 0.468 | 2.0 | 306 | 0.4210 | 0.8167 |
| 0.2216 | 3.0 | 459 | 0.4649 | 0.8183 |
| 0.1552 | 4.0 | 612 | 0.5008 | 0.8069 |
| 0.0962 | 5.0 | 765 | 0.7498 | 0.8347 |
| 0.0379 | 6.0 | 918 | 0.8682 | 0.8282 |
| 0.0026 | 7.0 | 1071 | 0.9450 | 0.8249 |
| 0.0202 | 8.0 | 1224 | 1.0202 | 0.8282 |
| 0.0011 | 9.0 | 1377 | 1.0601 | 0.8282 |
| 0.0305 | 10.0 | 1530 | 1.0660 | 0.8232 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1