Neuro_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: 0.0286
- Rmse: 0.1690
- Mae: 0.1342
- Corr: 0.4255
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 | 0.0260 | 0.1612 | 0.1289 | 0.4432 |
| No log | 2.0 | 470 | 0.0270 | 0.1644 | 0.1325 | 0.4459 |
| 0.0356 | 3.0 | 705 | 0.0253 | 0.1591 | 0.1263 | 0.4577 |
| 0.0356 | 4.0 | 940 | 0.0262 | 0.1619 | 0.1295 | 0.4348 |
| 0.0182 | 5.0 | 1175 | 0.0286 | 0.1690 | 0.1342 | 0.4255 |
Framework versions
- Transformers 4.44.1
- Pytorch 1.11.0
- Datasets 2.12.0
- Tokenizers 0.19.1