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: 0.1703
• Accuracy: 0.9315
• F1: 0.9316

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
0.8038	1.0	250	0.2937	0.9095	0.9087
0.223	2.0	500	0.1875	0.927	0.9277
0.1549	3.0	750	0.1703	0.9315	0.9316

Framework versions

• Transformers 4.32.1
• Pytorch 2.1.0
• Datasets 2.14.5
• Tokenizers 0.13.3