distilbert-sql-timeout-classifier-with-features-4096

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

• Loss: 0.4014
• Accuracy: 0.9163

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: 2
• eval_batch_size: 2
• seed: 42
• 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
0.4772	1.0	3347	0.7204	0.8532
0.3896	2.0	6694	0.4502	0.8944
0.2344	3.0	10041	0.4014	0.9163

Framework versions

• Transformers 4.38.1
• Pytorch 2.2.1+cu121
• Datasets 2.17.1
• Tokenizers 0.15.2