DistilBERT-finetuned-on-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: 0.2180
• Accuracy: 0.9235
• F1: 0.9235

Model description

DiestilBERT is fine-tuned on emotions dataset. Click the following link to see how the model works: https://huggingface.co/spaces/Rahmat82/emotions_classifier

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: 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
0.8046	1.0	250	0.3115	0.9085	0.9081
0.2405	2.0	500	0.2180	0.9235	0.9235

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0