finetunedemotionmodel

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: 0.2228
• Accuracy: 0.926
• F1: 0.9260

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: 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
0.8524	1.0	250	0.3379	0.905	0.9005
0.2588	2.0	500	0.2228	0.926	0.9260

Framework versions

• Transformers 4.30.0
• Pytorch 2.3.0+cu121
• Datasets 2.19.0
• Tokenizers 0.13.3