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deberta-v3-large-finetuned-dagpap22-only-and-real
This model is a fine-tuned version of domenicrosati/deberta-v3-large-finetuned-dagpap22-only-and-real on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0008
- F1: 0.9999
- Precision: 1.0
- Recall: 0.9997
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: 6e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
|---|---|---|---|---|---|---|
| 0.0016 | 1.0 | 10567 | 0.0060 | 0.9982 | 0.9997 | 0.9967 |
| 0.0 | 2.0 | 21134 | 0.0008 | 0.9999 | 1.0 | 0.9997 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
