finetuned-bert-mrpc
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4465
- Accuracy: 0.8407
- F1: 0.8904
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5966 | 1.0 | 230 | 0.4827 | 0.7794 | 0.8594 |
| 0.3979 | 2.0 | 460 | 0.4488 | 0.8186 | 0.8799 |
| 0.2508 | 3.0 | 690 | 0.4465 | 0.8407 | 0.8904 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for Snape-v/finetuned-bert-mrpc
Base model
google-bert/bert-base-cased