bert-mrpc-best-model
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: 0.4829
- Accuracy: 0.8725
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: 4.212631982305625e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 115 | 0.4428 | 0.7990 |
| No log | 2.0 | 230 | 0.3700 | 0.8676 |
| No log | 3.0 | 345 | 0.4721 | 0.8554 |
| No log | 4.0 | 460 | 0.4829 | 0.8725 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for KutayMelih/bert-mrpc-best-model
Base model
google-bert/bert-base-uncased