---
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: DeBERTaV3_model
  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. -->

# DeBERTaV3_model

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: 0.1419
- Accuracy: 0.9615
- F1: 0.8400
- Precision: 0.875
- Recall: 0.8077

## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 26   | 0.3810          | 0.875    | 0.0    | 0.0       | 0.0    |
| No log        | 2.0   | 52   | 0.3740          | 0.875    | 0.0    | 0.0       | 0.0    |
| No log        | 3.0   | 78   | 0.3303          | 0.875    | 0.0    | 0.0       | 0.0    |
| No log        | 4.0   | 104  | 0.2997          | 0.875    | 0.0    | 0.0       | 0.0    |
| No log        | 5.0   | 130  | 0.2484          | 0.8894   | 0.2581 | 0.8       | 0.1538 |
| No log        | 6.0   | 156  | 0.1951          | 0.9375   | 0.6977 | 0.8824    | 0.5769 |
| No log        | 7.0   | 182  | 0.1752          | 0.9423   | 0.7273 | 0.8889    | 0.6154 |
| No log        | 8.0   | 208  | 0.1582          | 0.9519   | 0.7917 | 0.8636    | 0.7308 |
| No log        | 9.0   | 234  | 0.1449          | 0.9615   | 0.8400 | 0.875     | 0.8077 |
| No log        | 10.0  | 260  | 0.1419          | 0.9615   | 0.8400 | 0.875     | 0.8077 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1