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sbi-model
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: 0.5290
- F1: 0.8211
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 |
---|---|---|---|---|
1.813 | 1.0 | 40 | 1.5304 | 0.5227 |
1.2312 | 2.0 | 80 | 0.9138 | 0.7439 |
0.7428 | 3.0 | 120 | 0.6869 | 0.7518 |
0.5055 | 4.0 | 160 | 0.5766 | 0.8050 |
0.3581 | 5.0 | 200 | 0.5454 | 0.8052 |
0.2664 | 6.0 | 240 | 0.5208 | 0.8200 |
0.2145 | 7.0 | 280 | 0.5218 | 0.8241 |
0.1853 | 8.0 | 320 | 0.5290 | 0.8211 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Tokenizers 0.12.1