classification_model_albert
This model is a fine-tuned version of albert/albert-base-v1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2353
- Accuracy: 0.9224
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2452 | 1.0 | 1563 | 0.2077 | 0.9186 |
| 0.1795 | 2.0 | 3126 | 0.2353 | 0.9224 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3