xlm_r_base-finetuned_after_mrp-v2-ruby-galaxy-10

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xlm_r_base-finetuned_after_mrp-v2-ruby-galaxy-10

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: 0.4889
• Precision 0: 0.8751
• Precision 1: 0.8092
• Recall 0: 0.8680
• Recall 1: 0.8187
• F1 0: 0.8715
• F1 1: 0.8139
• Precision Weighted: 0.8483
• Recall Weighted: 0.848
• F1 Weighted: 0.8481
• F1 Macro: 0.8427

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
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 5

Training results

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1