distilbert-base-uncased-finetuned_emotion

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: 0.1585
• Accuracy: 0.9355
• F1: 0.9354

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: 32
• eval_batch_size: 32
• 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
0.5725	1.0	500	0.2059	0.926	0.9262
0.1697	2.0	1000	0.1585	0.9355	0.9354

Framework versions

• Transformers 4.57.1
• Pytorch 2.7.1+cu118
• Datasets 4.2.0
• Tokenizers 0.22.1