distilbert-base-uncased-finetuned-emotions

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1464
• Accuracy: 0.936
• F1: 0.9360

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: 64
• eval_batch_size: 64
• 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
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.1146	1.0	250	0.1659	0.9335	0.9340
0.1051	2.0	500	0.1464	0.936	0.9360

Framework versions

• Transformers 4.48.3
• Pytorch 2.6.0
• Datasets 3.3.2
• Tokenizers 0.21.0