layoutlm-funsd

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layoutlm-funsd

This model is a fine-tuned version of microsoft/layoutlm-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.7407
• Education: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5}
• Email: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}
• Github: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 0}
• Location: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
• Name: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}
• Name : {'precision': 0.2, 'recall': 0.5, 'f1': 0.28571428571428575, 'number': 2}
• Phone Number: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}
• Soft Skills: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 0}
• Technical Skills: {'precision': 0.2, 'recall': 0.35714285714285715, 'f1': 0.25641025641025644, 'number': 14}
• Overall Precision: 0.1176
• Overall Recall: 0.2
• Overall F1: 0.1481
• Overall Accuracy: 0.1475

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: 3e-05
• 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
• num_epochs: 3

Training results

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1