distilbert-base-uncased-finetuned-sst2

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: 0.3073
• Accuracy: 0.8830
• F1: 0.8830

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
0.6626	1.0	109	0.3359	0.8716	0.8714
0.2921	2.0	218	0.3073	0.8830	0.8830

Framework versions

• Transformers 4.38.1
• Pytorch 2.1.0+cu121
• Tokenizers 0.15.2