icdar23-entrydetector_plaintext

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icdar23-entrydetector_plaintext

This model is a fine-tuned version of HueyNemud/das22-10-camembert_pretrained on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0424
• Ebegin: {'precision': 0.9725125822686799, 'recall': 0.9447160586686725, 'f1': 0.9584128195345288, 'number': 2659}
• Eend: {'precision': 0.9570211189329382, 'recall': 0.9652466367713004, 'f1': 0.9611162790697675, 'number': 2676}
• Overall Precision: 0.9646
• Overall Recall: 0.9550
• Overall F1: 0.9598
• Overall Accuracy: 0.9923

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: 0.0001
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 7500

Training results

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.9.0
• Tokenizers 0.13.2