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: 0.1662
• Accuracy: 0.93
• F1: 0.9301

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: 256
• eval_batch_size: 256
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	63	0.2997	0.91	0.9095
No log	2.0	126	0.2031	0.924	0.9242
No log	3.0	189	0.1826	0.9275	0.9278
0.264	4.0	252	0.1668	0.93	0.9301
0.264	5.0	315	0.1662	0.93	0.9301

Framework versions

• Transformers 4.27.4
• Pytorch 1.13.1
• Datasets 2.11.0
• Tokenizers 0.13.3