deberta-v3-large-test-ver2
This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0883
- Precision: 0.9894
- Recall: 0.9894
- F1: 0.9894
- Accuracy: 0.9894
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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.1048 | 1.0 | 1195 | 0.0778 | 0.9849 | 0.9849 | 0.9849 | 0.9849 |
0.0364 | 2.0 | 2390 | 0.0856 | 0.9824 | 0.9824 | 0.9824 | 0.9824 |
0.0218 | 3.0 | 3585 | 0.0863 | 0.9874 | 0.9874 | 0.9874 | 0.9874 |
0.0043 | 4.0 | 4780 | 0.0959 | 0.9872 | 0.9872 | 0.9872 | 0.9872 |
0.0011 | 5.0 | 5975 | 0.0883 | 0.9894 | 0.9894 | 0.9894 | 0.9894 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.2
- Datasets 2.19.0
- Tokenizers 0.19.1
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