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cscscsds/0320_cosmetic2_roberta

sourceHugging Faceupdated 3y agoView on Hugging Face

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0320cosmetic2roberta

This model is a fine-tuned version of klue/roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

—Loss: 0.4218
—Accuracy: 0.8535
—F1: 0.8554
—Precision: 0.8632
—Recall: 0.8535

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
—trainbatchsize: 8
—evalbatchsize: 8
—seed: 42
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—lrschedulerwarmup_steps: 500
—num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.4995	1.0	273	0.3611	0.8713	0.8724	0.8767	0.8713
0.4616	2.0	546	0.4809	0.8419	0.8435	0.8658	0.8419
0.2517	3.0	819	0.7009	0.8640	0.8651	0.8772	0.8640
0.6884	4.0	1092	0.7427	0.7978	0.8007	0.8425	0.7978
0.4318	5.0	1365	0.4725	0.8640	0.8647	0.8660	0.8640
0.2824	6.0	1638	0.6081	0.875	0.8759	0.8798	0.875
0.317	7.0	1911	0.5933	0.8676	0.8665	0.8672	0.8676
0.2067	8.0	2184	0.6951	0.8676	0.8671	0.8702	0.8676
0.037	9.0	2457	0.6081	0.8860	0.8851	0.8896	0.8860
0.1009	10.0	2730	0.7525	0.8640	0.8642	0.8651	0.8640

Framework versions

—Transformers 4.38.1
—Pytorch 2.2.1+cu121
—Datasets 2.17.1
—Tokenizers 0.15.2