---
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
datasets:
- autextification2023
metrics:
- accuracy
model-index:
- name: deberta-v3-small-autextification-adapter
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# deberta-v3-small-autextification-adapter

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the autextification2023 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6941
- Accuracy: 0.4874

## 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: 0.0001
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6969        | 1.0   | 3808 | 0.6930          | 0.5034   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1