distilbert-base-uncased-textclassification_ptuning

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: 0.2493
• Accuracy: 0.8983

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: 16
• eval_batch_size: 16
• 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
0.2545	1.0	1563	0.2501	0.8978
0.2592	2.0	3126	0.2493	0.8983

Framework versions

• PEFT 0.7.1
• Transformers 4.36.2
• Pytorch 2.0.0+cu117
• Datasets 2.16.1
• Tokenizers 0.15.0