bert-base-uncased-finetuned-small-0505
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: 1.8649
- Accuracy: 0.1818
- F1: 0.1182
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 | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 13 | 1.8337 | 0.1818 | 0.0559 |
| No log | 2.0 | 26 | 1.8559 | 0.2727 | 0.1414 |
| No log | 3.0 | 39 | 1.8488 | 0.1818 | 0.1010 |
| No log | 4.0 | 52 | 1.8649 | 0.1818 | 0.1182 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.10.3