distilbert-base-uncased-finetuned-ner-invoiceSenderName

• Loss: 0.0254
• Precision: 0.0
• Recall: 0.0
• F1: 0.0
• Accuracy: 0.9924

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

• 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
• num_epochs: 4

Training results

Framework versions

• Transformers 4.15.0
• Pytorch 1.10.1
• Datasets 2.3.2
• Tokenizers 0.10.3