emotion_classification_fr

This model is a fine-tuned version of 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