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outputs_test
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9518
- Accuracy: 0.7386
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: 8e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 12 | 0.7810 | 0.5943 |
| No log | 2.0 | 24 | 0.5357 | 0.6629 |
| No log | 3.0 | 36 | 0.4338 | 0.7129 |
| No log | 4.0 | 48 | 0.5672 | 0.6886 |
| No log | 5.0 | 60 | 0.7802 | 0.7114 |
| No log | 6.0 | 72 | 0.7019 | 0.73 |
| No log | 7.0 | 84 | 0.7304 | 0.7514 |
| No log | 8.0 | 96 | 1.0413 | 0.72 |
| No log | 9.0 | 108 | 0.8902 | 0.7314 |
| No log | 10.0 | 120 | 0.8441 | 0.7514 |
| No log | 11.0 | 132 | 0.7846 | 0.7643 |
| No log | 12.0 | 144 | 0.8730 | 0.7586 |
| No log | 13.0 | 156 | 0.9532 | 0.7386 |
| No log | 14.0 | 168 | 0.9541 | 0.74 |
| No log | 15.0 | 180 | 0.9518 | 0.7386 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
