ribesstefano/RuleBert-v0.5-k3

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ribesstefano/RuleBert-v0.5-k3

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

• —Loss: 0.3277
• —F1: 0.4513
• —Roc Auc: 0.6511
• —Accuracy: 0.0571

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-06
• —trainbatchsize: 2
• —evalbatchsize: 64
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —training_steps: 8000
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.36.2
• —Pytorch 2.1.0+cu121
• —Datasets 2.16.1
• —Tokenizers 0.15.0