---
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: text_classifier
  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. -->

# text_classifier

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2472
- Accuracy: 0.6158

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.4863        | 1.0   | 760   | 2.0973          | 0.2474   |
| 1.8132        | 2.0   | 1520  | 1.7995          | 0.4237   |
| 1.5143        | 3.0   | 2280  | 1.5842          | 0.5053   |
| 1.3095        | 4.0   | 3040  | 1.8946          | 0.5553   |
| 1.0743        | 5.0   | 3800  | 1.9189          | 0.5684   |
| 0.9554        | 6.0   | 4560  | 2.1748          | 0.5974   |
| 0.7778        | 7.0   | 5320  | 2.2701          | 0.6263   |
| 0.5849        | 8.0   | 6080  | 2.5282          | 0.6237   |
| 0.5472        | 9.0   | 6840  | 2.7330          | 0.6184   |
| 0.4232        | 10.0  | 7600  | 2.9518          | 0.6079   |
| 0.2858        | 11.0  | 8360  | 2.8892          | 0.6263   |
| 0.2908        | 12.0  | 9120  | 3.0251          | 0.6289   |
| 0.2391        | 13.0  | 9880  | 3.1414          | 0.6211   |
| 0.1569        | 14.0  | 10640 | 3.2581          | 0.6184   |
| 0.1405        | 15.0  | 11400 | 3.2472          | 0.6158   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0