distil-bert-fine-tuned-boolq

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: 0.9724
• Accuracy: 0.7125

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: 4
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.62	1.0	2357	0.6170	0.6865
0.5335	2.0	4714	0.5965	0.7107
0.4801	3.0	7071	0.9724	0.7125

Framework versions

• Transformers 4.39.3
• Pytorch 1.13.0
• Datasets 2.18.0
• Tokenizers 0.15.2