--- license: cc-by-nc-sa-4.0 base_model: microsoft/layoutlmv3-base tags: - generated_from_trainer datasets: - funsd-layoutlmv3 metrics: - precision - recall - f1 - accuracy model-index: - name: ft-ms-layoutlmv3-funsd-layoutlmv3 results: [] --- # ft-ms-layoutlmv3-funsd-layoutlmv3 This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the aisuko/funsd-layoutlmv3 dataset. It achieves the following results on the evaluation set: - Loss: 0.5755 - Precision: 0.8422 - Recall: 0.8803 - F1: 0.8608 - Accuracy: 0.8324 ## 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: 1e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 200 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 10.0 | 100 | 0.6104 | 0.8080 | 0.8614 | 0.8339 | 0.8262 | | No log | 20.0 | 200 | 0.5755 | 0.8422 | 0.8803 | 0.8608 | 0.8324 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.0.0 - Datasets 2.15.0 - Tokenizers 0.15.0