sentiment-model
This model is a fine-tuned version of prajjwal1/bert-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5607
- Accuracy: 0.7833
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: 5e-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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5278 | 1.0 | 1500 | 0.4808 | 0.7817 |
| 0.3811 | 2.0 | 3000 | 0.5271 | 0.78 |
| 0.3366 | 3.0 | 4500 | 0.5607 | 0.7833 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.12.1+cu102
- Datasets 2.12.0
- Tokenizers 0.12.1