xlm-roberta-large-ner-prostata-bs32

• Loss: 0.0236
• Precision: 0.9692
• Recall: 0.9761
• F1: 0.9726
• Accuracy: 0.9956

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

• learning_rate: 2e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 6
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.46.3
• Pytorch 2.11.0+cu128
• Datasets 3.0.1
• Tokenizers 0.20.3