distilbert-base-uncased-ner-invoiceSenderRecipient_clean_inv_28_02

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0266
• eval_precision: 0.9595
• eval_recall: 0.9642
• eval_f1: 0.9618
• eval_accuracy: 0.9957
• eval_runtime: 60.7498
• eval_samples_per_second: 271.474
• eval_steps_per_second: 16.971
• epoch: 9.98
• step: 58000

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
• num_epochs: 10
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.15.0
• Pytorch 1.13.1
• Datasets 2.3.2
• Tokenizers 0.10.3