distilbert-base-uncased-finetuned-Pre_requisite_finder_2

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: 0.4182
• Accuracy: 0.8130

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: 2.2534703769467627e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 37
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4523	1.0	863	0.4182	0.8130
0.4285	2.0	1726	0.4136	0.8130
0.4236	3.0	2589	0.4267	0.8130

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3