banking77-albert-base-v2
This model is a fine-tuned version of albert/albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3202
- Accuracy: 0.8729
- F1 Macro: 0.8712
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 93
- num_epochs: 3
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 2.5035 | 1.0 | 313 | 2.4883 | 0.6486 | 0.6193 |
| 1.4770 | 2.0 | 626 | 1.5055 | 0.8368 | 0.8285 |
| 1.2941 | 3.0 | 939 | 1.3202 | 0.8729 | 0.8712 |
Framework versions
- Transformers 5.6.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2