bert-base-uncased-finetuned-0505-2
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: 0.4277
- Accuracy: 0.9206
- F1: 0.9205
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 | 1373 | 0.3634 | 0.9025 | 0.9012 |
| No log | 2.0 | 2746 | 0.3648 | 0.9066 | 0.9060 |
| No log | 3.0 | 4119 | 0.3978 | 0.9189 | 0.9183 |
| No log | 4.0 | 5492 | 0.4277 | 0.9206 | 0.9205 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.10.3