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sbi-model-223
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5459
- F1: 0.8781
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: 8
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
0.146 | 1.0 | 38 | 0.5014 | 0.8525 |
0.0779 | 2.0 | 76 | 0.4644 | 0.8862 |
0.0432 | 3.0 | 114 | 0.5182 | 0.8811 |
0.0319 | 4.0 | 152 | 0.5121 | 0.8865 |
0.0356 | 5.0 | 190 | 0.5107 | 0.8894 |
0.024 | 6.0 | 228 | 0.5146 | 0.8867 |
0.0288 | 7.0 | 266 | 0.5281 | 0.8781 |
0.0277 | 8.0 | 304 | 0.5459 | 0.8781 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Tokenizers 0.13.1