TESTING
This model is a fine-tuned version of distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1167
- Precision: 0.9561
- Accuracy: 0.9592
- F1: 0.9592
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: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Accuracy | F1 |
---|---|---|---|---|---|---|
0.5903 | 0.4 | 500 | 0.4695 | 0.7342 | 0.7728 | 0.7890 |
0.3986 | 0.8 | 1000 | 0.3469 | 0.8144 | 0.8596 | 0.8684 |
0.2366 | 1.2 | 1500 | 0.1939 | 0.9313 | 0.9260 | 0.9253 |
0.1476 | 1.6 | 2000 | 0.1560 | 0.9207 | 0.9452 | 0.9465 |
0.1284 | 2.0 | 2500 | 0.1167 | 0.9561 | 0.9592 | 0.9592 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
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