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---
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
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