---
library_name: transformers
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
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: 0.3436
- Accuracy: 0.9520

## 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 | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.3919        | 0.2924 | 500  | 0.2821          | 0.9184   |
| 0.274         | 0.5848 | 1000 | 0.2795          | 0.9362   |
| 0.2552        | 0.8772 | 1500 | 0.2469          | 0.9355   |
| 0.2148        | 1.1696 | 2000 | 0.3214          | 0.9421   |
| 0.1876        | 1.4620 | 2500 | 0.2636          | 0.9382   |
| 0.1505        | 1.7544 | 3000 | 0.2323          | 0.9467   |
| 0.1411        | 2.0468 | 3500 | 0.3445          | 0.9395   |
| 0.0676        | 2.3392 | 4000 | 0.3280          | 0.9414   |
| 0.1089        | 2.6316 | 4500 | 0.4225          | 0.9270   |
| 0.0888        | 2.9240 | 5000 | 0.2458          | 0.9520   |
| 0.0544        | 3.2164 | 5500 | 0.2877          | 0.9539   |
| 0.0366        | 3.5088 | 6000 | 0.3010          | 0.9553   |
| 0.0322        | 3.8012 | 6500 | 0.3508          | 0.9474   |
| 0.0313        | 4.0936 | 7000 | 0.3302          | 0.9520   |
| 0.0191        | 4.3860 | 7500 | 0.3527          | 0.9493   |
| 0.0118        | 4.6784 | 8000 | 0.3378          | 0.9513   |
| 0.0189        | 4.9708 | 8500 | 0.3436          | 0.9520   |


### Framework versions

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