deberta-v3-large-test-ver1
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: 0.1156
- Precision: 0.9845
- Recall: 0.9845
- F1: 0.9845
- Accuracy: 0.9845
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 |
---|---|---|---|---|---|---|---|
0.0932 | 1.0 | 1589 | 0.0839 | 0.9778 | 0.9778 | 0.9778 | 0.9778 |
0.0675 | 2.0 | 3178 | 0.1071 | 0.9784 | 0.9784 | 0.9784 | 0.9784 |
0.0306 | 3.0 | 4767 | 0.0945 | 0.9820 | 0.9820 | 0.9820 | 0.9820 |
0.014 | 4.0 | 6356 | 0.1446 | 0.9799 | 0.9799 | 0.9799 | 0.9799 |
0.0084 | 5.0 | 7945 | 0.1156 | 0.9845 | 0.9845 | 0.9845 | 0.9845 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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