---
library_name: transformers
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mdeberta-v3-base-finetuned-french-green-stance
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mdeberta-v3-base-finetuned-french-green-stance

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3085
- Accuracy: 0.9533
- F1 Macro: 0.9428
- Accuracy Balanced: 0.9425
- F1 Micro: 0.9533
- Precision Macro: 0.9431
- Recall Macro: 0.9425
- Precision Micro: 0.9533
- Recall Micro: 0.9533

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Accuracy Balanced | F1 Micro | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
| 0.3304        | 1.0   | 1393 | 0.4028          | 0.9160   | 0.8984   | 0.9035            | 0.9160   | 0.8937          | 0.9035       | 0.9160          | 0.9160       |
| 0.2085        | 2.0   | 2786 | 0.2895          | 0.9440   | 0.9298   | 0.9201            | 0.9440   | 0.9410          | 0.9201       | 0.9440          | 0.9440       |
| 0.1368        | 3.0   | 4179 | 0.3136          | 0.9519   | 0.9408   | 0.9384            | 0.9519   | 0.9432          | 0.9384       | 0.9519          | 0.9519       |
| 0.0374        | 4.0   | 5572 | 0.3085          | 0.9533   | 0.9428   | 0.9425            | 0.9533   | 0.9431          | 0.9425       | 0.9533          | 0.9533       |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0