hemanthkotaprolu/distilbert-finetuned-emotion

distilbert-base-uncased-finetuned-emotion

This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset by following the book Natural Language Processing with Transformers by Leandro von Werra, Lewis Tunstall, and Thomas Wolf. It achieves the following results on the evaluation set:

• Loss: 0.4459
• Accuracy: 0.936
• F1: 0.9358

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: 128
• eval_batch_size: 128
• 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
No log	1.0	125	0.5699	0.9285	0.9299
No log	2.0	250	0.4599	0.93	0.9301
No log	3.0	375	0.4459	0.936	0.9358

Framework versions

• Transformers 4.41.2
• Pytorch 2.2.0a0+81ea7a4
• Datasets 2.20.0
• Tokenizers 0.19.1