BERT-Coursework
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4311
- Macro F1: 0.7720
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: 28
- 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 |
|---|---|---|---|---|
| 0.4627 | 1.0 | 1983 | 0.4428 | 0.7467 |
| 0.3917 | 2.0 | 3966 | 0.4155 | 0.7559 |
| 0.3374 | 3.0 | 5949 | 0.4171 | 0.7627 |
| 0.2939 | 4.0 | 7932 | 0.4311 | 0.7720 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2
- Downloads last month
- 4
Model tree for teotataru/BERT-Coursework
Base model
google-bert/bert-base-uncased