my-bert-classifier
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0018
- Accuracy: 1.0
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: 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
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0242 | 1.0 | 30 | 0.0089 | 1.0 |
| 0.0034 | 2.0 | 60 | 0.0022 | 1.0 |
| 0.0024 | 3.0 | 90 | 0.0018 | 1.0 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Tokenizers 0.21.1
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Model tree for singhshiva/my-bert-classifier
Base model
google-bert/bert-base-uncased