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emotion_classification_fr – AI Model by HikariLight | AlphaNeural AI
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emotion_classification_fr
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peft
safetensors
generated_from_trainer
FacebookAI/xlm-roberta-large
adapter
mit
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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
