tasinhoque/roberta-large-go-emotions

Text Classification GoEmotions

This model is a fine-tuned version of roberta-large on the go_emotions dataset. It achieves the following results on the test set (with a threshold of 0.15):

• Accuracy: 0.4175
• Precision: 0.4934
• Recall: 0.5621
• F1: 0.5102

Code

Code for training this model can be found here.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-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	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	0.088978	0.404349	0.480763	0.456827	0.444685
0.10620	2.0	0.082806	0.411353	0.460896	0.536386	0.486819
0.10620	3.0	0.081338	0.420199	0.519828	0.561297	0.522716

Framework versions

• Transformers 4.20.1
• Pytorch 1.12.0
• Datasets 2.1.0
• Tokenizers 0.12.1