Mit1208/UDOP-finetuned-DocLayNet

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

UDOP-finetuned-DocLayNet-3

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. It achieves the following results on the evaluation set:

• —eval_loss: 0.7407
• —eval_precision: 0.6058
• —eval_recall: 0.5870
• —eval_f1: 0.5962
• —eval_accuracy: 0.7863
• —eval_runtime: 16.2128
• —evalsamplesper_second: 3.886
• —evalstepsper_second: 1.974
• —epoch: 18.6
• —step: 800

Training procedure

### Training code: https://github.com/mit1280/Document-AI/blob/main/UDOPEncoderModelfinetuneDocLayNet.ipynb ### Inference code: https://github.com/mit1280/Document-AI/blob/main/UDOPDocLayNet_Inference.ipynb

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 2e-05
• —trainbatchsize: 2
• —evalbatchsize: 2
• —seed: 42
• —gradientaccumulationsteps: 8
• —totaltrainbatch_size: 16
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.1
• —training_steps: 1000

Framework versions

• —Transformers 4.39.0.dev0
• —Pytorch 2.2.1+cu121
• —Datasets 2.18.0
• —Tokenizers 0.15.2