---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: FIRE-deberta-v3-small-5epochs
  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. -->

# FIRE-deberta-v3-small-5epochs

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5989
- Accuracy: 0.8864
- F1: 0.8864
- Precision: 0.8864
- Recall: 0.8864

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4506        | 1.0   | 1091 | 0.5686          | 0.8791   | 0.8791 | 0.8791    | 0.8791 |
| 0.607         | 2.0   | 2182 | 0.5989          | 0.8864   | 0.8864 | 0.8864    | 0.8864 |
| 1.1603        | 3.0   | 3273 | 0.7154          | 0.8828   | 0.8828 | 0.8828    | 0.8828 |
| 0.541         | 4.0   | 4364 | 0.6804          | 0.8608   | 0.8608 | 0.8608    | 0.8608 |
| 0.0009        | 5.0   | 5455 | 0.7897          | 0.8718   | 0.8718 | 0.8718    | 0.8718 |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1