---
base_model: microsoft/deberta-v3-large
library_name: transformers
license: mit
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: panclef_data_deberta_finetuned
  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. -->

# panclef_data_deberta_finetuned

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the PAN CLEF 2025 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1185
- Accuracy: 0.9728
- Precision: 0.9735
- Recall: 0.9728
- F1: 0.9729

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3364        | 1.0   | 556  | 0.1755          | 0.9550   | 0.9572    | 0.9550 | 0.9552 |
| 0.2607        | 2.0   | 1112 | 0.2262          | 0.9347   | 0.9379    | 0.9347 | 0.9337 |
| 0.1895        | 3.0   | 1668 | 0.1562          | 0.9592   | 0.9619    | 0.9592 | 0.9595 |
| 0.1558        | 4.0   | 2224 | 0.1673          | 0.9627   | 0.9632    | 0.9627 | 0.9625 |
| 0.1617        | 5.0   | 2780 | 0.1505          | 0.9657   | 0.9659    | 0.9657 | 0.9658 |
| 0.1394        | 6.0   | 3336 | 0.1359          | 0.9632   | 0.9657    | 0.9632 | 0.9635 |
| 0.1354        | 7.0   | 3892 | 0.1310          | 0.9725   | 0.9725    | 0.9725 | 0.9725 |
| 0.1192        | 8.0   | 4448 | 0.1238          | 0.9683   | 0.9699    | 0.9683 | 0.9685 |
| 0.1096        | 9.0   | 5004 | 0.1222          | 0.9742   | 0.9744    | 0.9742 | 0.9742 |
| 0.1127        | 10.0  | 5560 | 0.1185          | 0.9728   | 0.9735    | 0.9728 | 0.9729 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1
- Datasets 3.0.0
- Tokenizers 0.20.1