classifier-chapter4

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

• Loss: 0.2499
• Accuracy: 0.9195
• F1: 0.9195

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: 5e-05
• train_batch_size: 32
• eval_batch_size: 32
• 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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	313	0.2770	0.9070	0.9067
0.3078	2.0	626	0.2499	0.9195	0.9195

Framework versions

• Transformers 4.48.1
• Pytorch 2.7.0.dev20250120
• Datasets 3.2.0
• Tokenizers 0.21.0