DistilRoberta
This model is a fine-tuned version of distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1246
- Precision: 0.9633
- Accuracy: 0.9697
- F1: 0.9705
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Accuracy | F1 |
---|---|---|---|---|---|---|
0.5894 | 0.4 | 500 | 0.4710 | 0.8381 | 0.7747 | 0.7584 |
0.3863 | 0.8 | 1000 | 0.3000 | 0.8226 | 0.8737 | 0.8858 |
0.2272 | 1.2 | 1500 | 0.1973 | 0.9593 | 0.9333 | 0.9329 |
0.1639 | 1.6 | 2000 | 0.1694 | 0.9067 | 0.9367 | 0.9403 |
0.1263 | 2.0 | 2500 | 0.1128 | 0.9657 | 0.9597 | 0.9603 |
0.0753 | 2.4 | 3000 | 0.1305 | 0.9614 | 0.967 | 0.9679 |
0.0619 | 2.8 | 3500 | 0.1246 | 0.9633 | 0.9697 | 0.9705 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
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