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: 0.1561
• Accuracy: 0.9385
• F1: 0.9388

Label description

• Label_0: sadness
• Label_1: joy
• Label_2: love
• Label_3: anger
• Label_4: fear
• Label_5: surprise

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

This model is finetuned on the emotion dataset.

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
0.1762	1.0	250	0.1719	0.929	0.9287
0.1157	2.0	500	0.1561	0.9385	0.9388

Framework versions

• Transformers 4.24.0
• Pytorch 2.0.0.dev20230215
• Datasets 2.9.0
• Tokenizers 0.11.0