results
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5933
- Accuracy: 0.8596
- F1: 0.8420
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6828 | 1.0 | 182 | 0.7011 | 0.6976 | 0.4393 |
| 0.4415 | 2.0 | 364 | 0.4868 | 0.8266 | 0.7933 |
| 0.4762 | 3.0 | 546 | 0.5500 | 0.8163 | 0.7798 |
| 0.2522 | 4.0 | 728 | 0.5855 | 0.8369 | 0.8139 |
| 0.1986 | 5.0 | 910 | 0.5933 | 0.8596 | 0.8420 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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