| | --- |
| | license: mit |
| | base_model: microsoft/deberta-v3-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: deberta_essay |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # deberta_essay |
| | |
| | This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/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 |
| | |
