Trust_continuous
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: 0.0731
- Rmse: 0.2703
- Mae: 0.2142
- Corr: 0.2905
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: 32
- eval_batch_size: 32
- seed: 1234
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rmse | Mae | Corr |
|---|---|---|---|---|---|---|
| No log | 1.0 | 235 | 0.0491 | 0.2215 | 0.1788 | 0.2797 |
| No log | 2.0 | 470 | 0.0487 | 0.2206 | 0.1753 | 0.3103 |
| 0.0595 | 3.0 | 705 | 0.0476 | 0.2181 | 0.1731 | 0.3402 |
| 0.0595 | 4.0 | 940 | 0.0629 | 0.2508 | 0.1980 | 0.3145 |
| 0.039 | 5.0 | 1175 | 0.0731 | 0.2703 | 0.2142 | 0.2905 |
Framework versions
- Transformers 4.44.1
- Pytorch 1.11.0
- Datasets 2.12.0
- Tokenizers 0.19.1