LayoutLMv3-DocLayNet-small

This model is a fine-tuned version of microsoft/layoutlmv3-base on the doc_lay_net-small dataset. It achieves the following results on the evaluation set:

• Loss: 1.2781
• Precision: 0.1283
• Recall: 0.0759
• F1: 0.0954
• Accuracy: 0.6477

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: 4
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 16
• total_train_batch_size: 256
• total_eval_batch_size: 16
• optimizer: Use adamw_torch 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: 3.0

Training results

Framework versions

• Transformers 4.51.3
• Pytorch 2.4.1
• Datasets 3.5.1
• Tokenizers 0.21.1