| | --- |
| | license: cc-by-nc-sa-4.0 |
| | base_model: microsoft/layoutlmv3-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: layoutLMv3-finetuned-confluence |
| | results: [] |
| | --- |
| | |
| | <!-- 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-finetuned-confluence |
| |
|
| | This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.1354 |
| | - Precision: 0.8992 |
| | - Recall: 0.9126 |
| | - F1: 0.9058 |
| | - Accuracy: 0.8578 |
| |
|
| | ## 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: 5 |
| | - eval_batch_size: 5 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - training_steps: 2500 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | No log | 8.33 | 250 | 0.9563 | 0.8807 | 0.9056 | 0.8930 | 0.8505 | |
| | | 0.0199 | 16.67 | 500 | 1.0827 | 0.8792 | 0.9041 | 0.8915 | 0.8393 | |
| | | 0.0199 | 25.0 | 750 | 1.0539 | 0.8834 | 0.9036 | 0.8934 | 0.8493 | |
| | | 0.0048 | 33.33 | 1000 | 1.1217 | 0.8944 | 0.9131 | 0.9036 | 0.8583 | |
| | | 0.0048 | 41.67 | 1250 | 1.1195 | 0.9004 | 0.9071 | 0.9037 | 0.8616 | |
| | | 0.0025 | 50.0 | 1500 | 1.1927 | 0.8923 | 0.9056 | 0.8989 | 0.8467 | |
| | | 0.0025 | 58.33 | 1750 | 1.1155 | 0.9017 | 0.9116 | 0.9066 | 0.8640 | |
| | | 0.0008 | 66.67 | 2000 | 1.1871 | 0.8971 | 0.9056 | 0.9014 | 0.8395 | |
| | | 0.0008 | 75.0 | 2250 | 1.1709 | 0.9007 | 0.9106 | 0.9056 | 0.8420 | |
| | | 0.0006 | 83.33 | 2500 | 1.1354 | 0.8992 | 0.9126 | 0.9058 | 0.8578 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.38.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| |
|
