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ppak10/defect-classification-distilbert-baseline-15-epochs

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face

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defect-classification-distilbert-baseline-15-epochs

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: 0.2980
—Accuracy: 0.8765

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
—trainbatchsize: 512
—evalbatchsize: 512
—seed: 42
—optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
—lrschedulertype: linear
—num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7058	1.0	1062	0.6084	0.7927
0.5439	2.0	2124	0.4581	0.8141
0.4417	3.0	3186	0.3951	0.8403
0.4504	4.0	4248	0.3578	0.8487
0.428	5.0	5310	0.3352	0.8584
0.4089	6.0	6372	0.3347	0.8638
0.3428	7.0	7434	0.3248	0.8681
0.4219	8.0	8496	0.3178	0.8715
0.3689	9.0	9558	0.3044	0.8736
0.3891	10.0	10620	0.3037	0.8724
0.3849	11.0	11682	0.3064	0.8713
0.3302	12.0	12744	0.3006	0.8758
0.3576	13.0	13806	0.3016	0.8742
0.3548	14.0	14868	0.2990	0.8766
0.3596	15.0	15930	0.2980	0.8765

Framework versions

—Transformers 4.47.0
—Pytorch 2.5.1+cu124
—Datasets 3.2.0
—Tokenizers 0.21.0