bert-banking77-classifier-lora
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6999
- F1: 0.8264
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: 0.0002
- train_batch_size: 32
- eval_batch_size: 16
- 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
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 2.3431 | 1.0 | 313 | 2.1174 | 0.3925 |
| 1.3737 | 2.0 | 626 | 1.2632 | 0.6508 |
| 0.9534 | 3.0 | 939 | 0.9034 | 0.7581 |
| 0.7365 | 4.0 | 1252 | 0.7530 | 0.8130 |
| 0.6526 | 5.0 | 1565 | 0.6999 | 0.8264 |
Framework versions
- PEFT 0.10.0
- Transformers 4.49.0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0
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Base model
google-bert/bert-base-uncased