my-finetuned-emotion-distilbert

• Loss: 0.4044
• Accuracy: 0.8360
• F1: 0.8351
• Precision: 0.8350
• Recall: 0.8360
• Classification Report: precision recall f1-score support
  Class 0 0.84 0.87 0.86 87 Class 1 0.85 0.87 0.86 268 Class 2 0.80 0.75 0.77 151
  accuracy 0.84 506 macro avg 0.83 0.83 0.83 506 weighted avg 0.84 0.84 0.84 506

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

• learning_rate: 2e-05
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

 Class 0       0.83      0.78      0.80        87
 Class 1       0.80      0.89      0.84       268
 Class 2       0.76      0.64      0.70       151

accuracy                           0.80       506

 Class 0       0.84      0.87      0.86        87
 Class 1       0.85      0.87      0.86       268
 Class 2       0.80      0.75      0.77       151

accuracy                           0.84       506

Framework versions

• Transformers 4.41.2
• Pytorch 2.2.2
• Datasets 2.20.0
• Tokenizers 0.19.1