binary_classifier

This model is a fine-tuned version of distilbert/distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6459
• Accuracy: 1.0

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6437	1.0	9	0.6773	0.6667
0.65	2.0	18	0.6628	1.0
0.6561	3.0	27	0.6575	1.0
0.6398	4.0	36	0.6532	1.0
0.6594	5.0	45	0.6516	1.0

Framework versions

• Transformers 4.46.3
• Pytorch 2.5.1+cpu
• Datasets 3.1.0
• Tokenizers 0.20.3