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: 0.2162
• Accuracy: 0.9225
• F1: 0.9227

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
0.8437	1.0	250	0.3153	0.903	0.9005
0.2467	2.0	500	0.2162	0.9225	0.9227

Framework versions

• Transformers 4.16.2
• Pytorch 1.10.2+cpu
• Datasets 1.18.3
• Tokenizers 0.11.0