lab6-trained

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: 0.5275
• Accuracy: 0.8730
• F1: 0.8648

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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
0.6194	1.0	547	0.5117	0.8677	0.8630
0.2676	2.0	1094	0.5275	0.8730	0.8648

Framework versions

• Transformers 5.14.1
• Pytorch 2.9.1+cu128
• Datasets 5.0.0
• Tokenizers 0.22.2