bert-sdg-classification
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: 0.7055
- F1: 0.7980
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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
- lr_scheduler_warmup_steps: 600
- num_epochs: 5.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 2.2299 | 1.0 | 538 | 1.0520 | 0.7118 |
| 0.9383 | 2.0 | 1076 | 0.7800 | 0.7794 |
| 0.7379 | 3.0 | 1614 | 0.7253 | 0.7947 |
| 0.6362 | 4.0 | 2152 | 0.7107 | 0.7965 |
| 0.5779 | 5.0 | 2690 | 0.7055 | 0.7980 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.1.2.post304
- Datasets 3.2.0
- Tokenizers 0.21.0