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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: 0.0380
- Pearson: 0.9399
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: 256
- 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson |
|---|---|---|---|---|
| No log | 1.0 | 12 | 0.2773 | 0.7230 |
| No log | 2.0 | 24 | 0.1120 | 0.7812 |
| No log | 3.0 | 36 | 0.1090 | 0.8638 |
| No log | 4.0 | 48 | 0.0613 | 0.9163 |
| No log | 5.0 | 60 | 0.0447 | 0.9409 |
| No log | 6.0 | 72 | 0.0356 | 0.9402 |
| No log | 7.0 | 84 | 0.0368 | 0.9359 |
| No log | 8.0 | 96 | 0.0408 | 0.9295 |
| No log | 9.0 | 108 | 0.0397 | 0.9382 |
| No log | 10.0 | 120 | 0.0380 | 0.9399 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2
