distilbert-base-uncased-finetuned-emotion

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

• Loss: 0.2033
• Accuracy: 0.9275
• F1: 0.9273

Model description

This model is a copy of the model found in the book Natural Language Processing with Transformers.

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
0.806	1.0	250	0.2954	0.908	0.9062
0.2361	2.0	500	0.2033	0.9275	0.9273

Framework versions

• Transformers 4.13.0
• Pytorch 1.12.1+cu113
• Datasets 1.16.1
• Tokenizers 0.10.3