| | --- |
| | library_name: transformers |
| | license: cc-by-nc-sa-4.0 |
| | base_model: microsoft/layoutlmv3-base |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - doc_lay_net-small |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: LayoutLMv3-DocLayNet-small |
| | results: |
| | - task: |
| | name: Token Classification |
| | type: token-classification |
| | dataset: |
| | name: doc_lay_net-small |
| | type: doc_lay_net-small |
| | config: DocLayNet_2022.08_processed_on_2023.01 |
| | split: validation |
| | args: DocLayNet_2022.08_processed_on_2023.01 |
| | metrics: |
| | - name: Precision |
| | type: precision |
| | value: 0.12834224598930483 |
| | - name: Recall |
| | type: recall |
| | value: 0.0759493670886076 |
| | - name: F1 |
| | type: f1 |
| | value: 0.09542743538767395 |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.6476804585348379 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # LayoutLMv3-DocLayNet-small |
| |
|
| | This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/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 |
| | |
