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livinNector/m-minilm-l12-h384-dra-tam-mal-aw-setfit-double-finetune

sourceHugging Faceupdated 2y agoView on Hugging Face

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m-minilm-l12-h384-dra-tam-mal-aw-setfit-double-finetune

This model is a fine-tuned version of livinNector/m-minilm-l12-h384-dra-tam-mal-aw-setfit-finetune on the None dataset. It achieves the following results on the evaluation set:

—Loss: 0.5252
—Accuracy: 0.7759
—F1: 0.7752

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: 0.0001
—trainbatchsize: 128
—evalbatchsize: 128
—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: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6682	0.4444	20	0.6228	0.6659	0.6625
0.6171	0.8889	40	0.6035	0.6789	0.6756
0.5673	1.3333	60	0.5673	0.7188	0.7155
0.5481	1.7778	80	0.5864	0.6993	0.6937
0.5137	2.2222	100	0.5245	0.7465	0.7440
0.4527	2.6667	120	0.5279	0.7522	0.7506
0.4596	3.1111	140	0.5172	0.7579	0.7576
0.3943	3.5556	160	0.5366	0.7514	0.7514
0.3836	4.0	180	0.5387	0.7628	0.7627
0.3627	4.4444	200	0.5802	0.7490	0.7480
0.3302	4.8889	220	0.5616	0.7563	0.7563
0.2999	5.3333	240	0.5745	0.7620	0.7598
0.3061	5.7778	260	0.5651	0.7694	0.7689

Framework versions

—Transformers 4.47.1
—Pytorch 2.5.1+cu124
—Datasets 3.2.0
—Tokenizers 0.21.0