results

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

• Loss: 0.2147
• Accuracy: 0.925
• F1: 0.9251

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.8221	1.0	250	0.3106	0.9125	0.9102
0.2537	2.0	500	0.2147	0.925	0.9251

Framework versions

• Transformers 4.11.3
• Pytorch 1.9.1+cu102
• Datasets 1.13.0
• Tokenizers 0.10.3