---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: deberta_biodiversite
  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. -->

# deberta_biodiversite

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0237
- Accuracy: 0.9926
- F1: 0.9927

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.2788        | 1.0   | 128  | 0.6534          | 0.7828   | 0.7762 |
| 0.5887        | 2.0   | 256  | 0.3681          | 0.8926   | 0.8884 |
| 0.4035        | 3.0   | 384  | 0.2719          | 0.9142   | 0.9123 |
| 0.2674        | 4.0   | 512  | 0.1562          | 0.9564   | 0.9563 |
| 0.2189        | 5.0   | 640  | 0.1438          | 0.9613   | 0.9610 |
| 0.152         | 6.0   | 768  | 0.1300          | 0.9701   | 0.9701 |
| 0.1403        | 7.0   | 896  | 0.0879          | 0.9794   | 0.9792 |
| 0.1072        | 8.0   | 1024 | 0.0673          | 0.9873   | 0.9872 |
| 0.1236        | 9.0   | 1152 | 0.0499          | 0.9887   | 0.9887 |
| 0.0803        | 10.0  | 1280 | 0.0490          | 0.9907   | 0.9907 |
| 0.0746        | 11.0  | 1408 | 0.0501          | 0.9912   | 0.9912 |
| 0.0568        | 12.0  | 1536 | 0.0314          | 0.9912   | 0.9912 |
| 0.0397        | 13.0  | 1664 | 0.0285          | 0.9917   | 0.9916 |
| 0.0445        | 14.0  | 1792 | 0.0204          | 0.9926   | 0.9927 |
| 0.0479        | 15.0  | 1920 | 0.0250          | 0.9922   | 0.9922 |
| 0.0363        | 16.0  | 2048 | 0.0244          | 0.9922   | 0.9922 |
| 0.0343        | 17.0  | 2176 | 0.0237          | 0.9926   | 0.9927 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0