---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dignity-classifier-base
  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. -->

# dignity-classifier-base

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: 0.6340
- Accuracy: 0.8391

## 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: 5e-05
- train_batch_size: 32
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7117        | 1.0   | 98   | 0.6658          | 0.7328   |
| 0.4678        | 2.0   | 196  | 0.5435          | 0.7816   |
| 0.2648        | 3.0   | 294  | 0.5548          | 0.8132   |
| 0.1378        | 4.0   | 392  | 0.5295          | 0.8362   |
| 0.0561        | 5.0   | 490  | 0.6340          | 0.8391   |


### Framework versions

- Transformers 4.29.2
- Pytorch 1.13.1
- Datasets 2.12.0
- Tokenizers 0.13.3