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

# my_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: 0.1746
- Accuracy: 0.9589
- F1: 0.8034
- Precision: 1.0
- Recall: 0.6714

## 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   | 14   | 0.4759          | 0.875    | 0.0    | 0.0       | 0.0    |
| No log        | 2.0   | 28   | 0.3609          | 0.875    | 0.0    | 0.0       | 0.0    |
| No log        | 3.0   | 42   | 0.3394          | 0.875    | 0.0    | 0.0       | 0.0    |
| No log        | 4.0   | 56   | 0.3070          | 0.875    | 0.0    | 0.0       | 0.0    |
| No log        | 5.0   | 70   | 0.2768          | 0.875    | 0.0    | 0.0       | 0.0    |
| No log        | 6.0   | 84   | 0.2432          | 0.8893   | 0.2051 | 1.0       | 0.1143 |
| No log        | 7.0   | 98   | 0.2159          | 0.9071   | 0.4091 | 1.0       | 0.2571 |
| No log        | 8.0   | 112  | 0.1946          | 0.9429   | 0.7037 | 1.0       | 0.5429 |
| No log        | 9.0   | 126  | 0.1798          | 0.9554   | 0.7826 | 1.0       | 0.6429 |
| No log        | 10.0  | 140  | 0.1746          | 0.9589   | 0.8034 | 1.0       | 0.6714 |


### Framework versions

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