anpmts/xlm-roberta-quality-classifier

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xlm-roberta-quality-classifier

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

• —Accuracy: 0.9815
• —F1: 0.9817
• —F1 High: 0.9741
• —F1 Low: 0.9989
• —F1 Medium: 0.9720
• —Loss: 0.0651
• —Precision: 0.9818
• —Recall: 0.9816

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: 2.0000000000000003e-06
• —trainbatchsize: 96
• —evalbatchsize: 256
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 2
• —totaltrainbatch_size: 192
• —totalevalbatch_size: 512
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 10
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.57.1
• —Pytorch 2.9.0+cu128
• —Datasets 4.3.0
• —Tokenizers 0.22.1