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Surbhipatil/token_classification_NER

sourceHugging Faceapache-2.0updated 8d agoView on Hugging Face

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tokenclassificationNER

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: 0.2843
—Precision: 0.5375
—Recall: 0.3920
—F1: 0.4534
—Accuracy: 0.9466

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: 16
—evalbatchsize: 16
—seed: 42
—optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
—lrschedulertype: linear
—num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	213	0.2777	0.6327	0.2651	0.3736	0.9396
No log	2.0	426	0.2499	0.5356	0.3698	0.4375	0.9437
0.1938	3.0	639	0.2813	0.5947	0.3522	0.4424	0.9457
0.1938	4.0	852	0.2752	0.5637	0.3939	0.4637	0.9471
0.0532	5.0	1065	0.2843	0.5375	0.3920	0.4534	0.9466

Framework versions

—Transformers 4.53.3
—Pytorch 2.11.0+cu128
—Datasets 4.0.0
—Tokenizers 0.21.4