distilbert-base-uncased-finetuned-emotion-imbalanced-1000plus3000

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

• Loss: 1.1446
• Accuracy: 0.5835
• F1: 0.4990

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
1.4611	1.0	63	1.2669	0.532	0.4233
1.1433	2.0	126	1.1446	0.5835	0.4990

Framework versions

• Transformers 4.16.2
• Pytorch 2.1.0+cu121
• Datasets 1.16.1
• Tokenizers 0.15.0