distilbert-base-uncased-finetuned-emotion

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: 0.1581
• Accuracy: 0.9365
• F1: 0.9365

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.7694	1.0	250	0.2602	0.9195	0.9178
0.2098	2.0	500	0.1733	0.927	0.9271
0.1463	3.0	750	0.1581	0.9365	0.9365

Framework versions

• Transformers 4.13.0
• Pytorch 1.13.1+cu116
• Datasets 2.8.0
• Tokenizers 0.10.3