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: 0.1671
• Accuracy: 0.939
• F1: 0.9393

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

Labels:

0: sadness

1: joy

2: love

3: anger

4: fear

5: surprise

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
0.0891	1.0	250	0.1825	0.931	0.9310
0.0738	2.0	500	0.1671	0.939	0.9393

Framework versions

• Transformers 4.16.2
• Pytorch 2.1.0+cu118
• Datasets 1.16.1
• Tokenizers 0.15.0