text_analyzer_albert-base-v2
This model is a fine-tuned version of albert-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0093
- Accuracy: 0.9988
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: 1
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.4321 | 1.0 | 3457 | 0.3820 | 0.9341 |
| 0.1756 | 2.0 | 6914 | 0.1220 | 0.9815 |
| 0.029 | 3.0 | 10371 | 0.0464 | 0.9919 |
| 0.0001 | 4.0 | 13828 | 0.0093 | 0.9988 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.12.0+cu102
- Datasets 2.13.1
- Tokenizers 0.13.3