Modelpublic

nosnelmil/RoBERTa-CompareTransformers-Imdb

sourceHugging Facemitupdated 3y agoView on Hugging Face

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results

This model is a fine-tuned version of roberta-base on the imdb dataset. It achieves the following results on the evaluation set:

—Loss: 0.2691
—Accuracy: 0.9287
—Precision: 0.9287
—Recall: 0.9287
—F1: 0.9287
—Auroc: 0.9772

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: 4
—evalbatchsize: 4
—seed: 42
—distributed_type: multi-GPU
—gradientaccumulationsteps: 4
—totaltrainbatch_size: 16
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Auroc
0.1764	0.46	500	0.2698	0.9044	0.9044	0.9044	0.9044	0.9738
0.3348	0.91	1000	0.2755	0.9117	0.9117	0.9117	0.9117	0.9686
0.1478	1.37	1500	0.3275	0.9109	0.9109	0.9109	0.9109	0.9771
0.2051	1.83	2000	0.2575	0.9309	0.9309	0.9309	0.9309	0.9793
0.1435	2.29	2500	0.3140	0.9245	0.9245	0.9245	0.9245	0.9783
0.1425	2.74	3000	0.2691	0.9287	0.9287	0.9287	0.9287	0.9772

Framework versions

—Transformers 4.34.1
—Pytorch 2.1.0+cu118
—Datasets 2.14.6
—Tokenizers 0.14.1