---
base_model: FacebookAI/xlm-roberta-large
library_name: peft
license: mit
metrics:
- accuracy
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: emotion_classification_fr
  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. -->

# emotion_classification_fr

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5239
- Accuracy: 0.815
- Precision: 0.8165
- Recall: 0.815
- F1-score: 0.8152

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1-score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 0.6944        | 1.0   | 1000 | 0.6852          | 0.76     | 0.7601    | 0.76   | 0.7584   |
| 0.7167        | 2.0   | 2000 | 0.5862          | 0.798    | 0.8032    | 0.798  | 0.7994   |
| 0.5138        | 3.0   | 3000 | 0.5239          | 0.815    | 0.8165    | 0.815  | 0.8152   |


### Framework versions

- PEFT 0.13.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1