metadata
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta_essay
results: []
deberta_essay
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: 0.3744
- Mse: 0.3744
- Mae: 0.4721
- R2: 0.6503
- Accuracy: 0.2651
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4178 | 1.0 | 1731 | 0.3564 | 0.3564 | 0.4600 | 0.6672 | 0.2637 |
| 0.3334 | 2.0 | 3462 | 0.4004 | 0.4004 | 0.4846 | 0.6261 | 0.2611 |
| 0.2403 | 3.0 | 5193 | 0.3286 | 0.3286 | 0.4445 | 0.6931 | 0.2630 |
| 0.1817 | 4.0 | 6924 | 0.3319 | 0.3319 | 0.4422 | 0.6900 | 0.2717 |
| 0.1207 | 5.0 | 8655 | 0.3744 | 0.3744 | 0.4721 | 0.6503 | 0.2651 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2