NF4-KD-NID

This model is a fine-tuned version of huawei-noah/TinyBERT_General_4L_312D on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0419
• Accuracy: 0.9919
• Precision: 0.9744
• Recall: 0.9469
• F1 score: 0.9546

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: 650
• eval_batch_size: 650
• 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: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1 score
0.2112	1.0	1828	0.1824	0.9775	0.7759	0.7784	0.7742
0.1196	2.0	3656	0.1061	0.9850	0.9060	0.8522	0.8502
0.0956	3.0	5484	0.0855	0.9874	0.9140	0.8833	0.8858
0.0823	4.0	7312	0.0708	0.9891	0.9204	0.8982	0.9029
0.0653	5.0	9140	0.0628	0.9897	0.9313	0.8985	0.9070
0.066	6.0	10968	0.0572	0.9901	0.9206	0.9132	0.9106
0.0546	7.0	12796	0.0534	0.9907	0.9284	0.9156	0.9187
0.0486	8.0	14624	0.0511	0.9909	0.9287	0.9184	0.9199
0.0473	9.0	16452	0.0490	0.9911	0.9732	0.9284	0.9346
0.0483	10.0	18280	0.0469	0.9914	0.9788	0.9237	0.9344
0.0435	11.0	20108	0.0451	0.9915	0.9722	0.9323	0.9360
0.0388	12.0	21936	0.0429	0.9917	0.9757	0.9395	0.9477
0.039	13.0	23764	0.0426	0.9917	0.9758	0.9514	0.9597
0.0362	14.0	25592	0.0423	0.9918	0.9743	0.9467	0.9542
0.0357	15.0	27420	0.0419	0.9919	0.9744	0.9469	0.9546

Framework versions

• Transformers 4.49.0
• Pytorch 2.6.0+cu124
• Datasets 3.4.1
• Tokenizers 0.21.1