Kuongan/CS221-xlm-roberta-base-chn-noaug-finetuned-chn-tapt

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CS221-xlm-roberta-base-chn-noaug-finetuned-chn-tapt

This model is a fine-tuned version of Kuongan/xlm-roberta-base-chn-noaug on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.0827
• —F1: 0.8367
• —Roc Auc: 0.9048
• —Accuracy: 0.8596

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: 32
• —evalbatchsize: 32
• —seed: 42
• —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_steps: 100
• —num_epochs: 20

Training results

Framework versions

• —Transformers 4.47.0
• —Pytorch 2.5.1+cu121
• —Datasets 3.2.0
• —Tokenizers 0.21.0