BP-INT03
This model is a fine-tuned version of prajjwal1/bert-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3220
- Accuracy: 0.89
- F1: 0.8889
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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 0.0 | 50 | 0.6958 | 0.43 | 0.2586 |
No log | 0.01 | 100 | 0.6890 | 0.67 | 0.6043 |
No log | 0.01 | 150 | 0.6814 | 0.57 | 0.4139 |
No log | 0.02 | 200 | 0.6723 | 0.57 | 0.4139 |
No log | 0.02 | 250 | 0.6289 | 0.81 | 0.8103 |
No log | 0.03 | 300 | 0.5298 | 0.82 | 0.8207 |
No log | 0.03 | 350 | 0.4480 | 0.88 | 0.8796 |
No log | 0.04 | 400 | 0.4042 | 0.89 | 0.8889 |
No log | 0.04 | 450 | 0.3688 | 0.9 | 0.8988 |
0.6099 | 0.05 | 500 | 0.3615 | 0.89 | 0.8889 |
0.6099 | 0.05 | 550 | 0.3542 | 0.89 | 0.8889 |
0.6099 | 0.06 | 600 | 0.3443 | 0.89 | 0.8889 |
0.6099 | 0.06 | 650 | 0.3300 | 0.89 | 0.8889 |
0.6099 | 0.07 | 700 | 0.3196 | 0.89 | 0.8889 |
0.6099 | 0.07 | 750 | 0.3220 | 0.89 | 0.8889 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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