bert-emotion-clf

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

• Loss: 0.1641
• F1: 0.9318

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: 5e-05
• train_batch_size: 16
• eval_batch_size: 8
• 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	F1
0.1951	1.0	1000	0.1886	0.9328
0.1353	2.0	2000	0.1450	0.9379
0.0826	3.0	3000	0.1641	0.9318

Framework versions

• Transformers 4.27.1
• Pytorch 2.2.1+cu121
• Datasets 2.9.0
• Tokenizers 0.13.3