---
library_name: transformers
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: deberta_textclassification
  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_textclassification

This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5291
- Accuracy: 0.9043
- F1: 0.9320

## 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: 16
- eval_batch_size: 16
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4082        | 1.0   | 760  | 0.3256          | 0.8720   | 0.9050 |
| 0.2193        | 2.0   | 1520 | 0.2805          | 0.8967   | 0.9259 |
| 0.1571        | 3.0   | 2280 | 0.3280          | 0.9089   | 0.9357 |
| 0.0947        | 4.0   | 3040 | 0.4283          | 0.9112   | 0.9368 |
| 0.0489        | 5.0   | 3800 | 0.5291          | 0.9043   | 0.9320 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.4.0
- Tokenizers 0.19.1