bert-airline-full
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: 0.7740
- Accuracy: 0.8538
- Macro F1: 0.8109
- Weighted F1: 0.8535
- Precision: 0.8118
- Recall: 0.8102
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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 500
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|---|
| 0.9773 | 1.0 | 321 | 0.8968 | 0.8288 | 0.7879 | 0.8319 | 0.7766 | 0.8016 |
| 0.8435 | 2.0 | 642 | 0.7741 | 0.8543 | 0.8117 | 0.8539 | 0.8125 | 0.8111 |
| 0.5050 | 3.0 | 963 | 0.8140 | 0.8525 | 0.8091 | 0.8531 | 0.8045 | 0.8139 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2