---
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