haturusinghe/xlm_r_base-finetuned_after_mrp-v2-efficient-jazz-2

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xlmrbase-finetunedaftermrp-v2-efficient-jazz-2

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

• —Loss: 0.4290
• —Precision 0: 0.8620
• —Precision 1: 0.7980
• —Recall 0: 0.8620
• —Recall 1: 0.7980
• —F1 0: 0.8620
• —F1 1: 0.7980
• —Precision Weighted: 0.836
• —Recall Weighted: 0.836
• —F1 Weighted: 0.836
• —Accuracy: 0.836
• —F1 Macro: 0.8300

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: 16
• —evalbatchsize: 16
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 5

Training results

Framework versions

• —Transformers 4.41.1
• —Pytorch 2.3.0+cu121
• —Datasets 2.19.1
• —Tokenizers 0.19.1