| --- |
| license: cc-by-nc-sa-4.0 |
| base_model: microsoft/layoutlmv3-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: doc_classification |
| 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. --> |
|
|
| # doc_classification |
| |
| 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: 0.0056 |
| - Precision: 1.0 |
| - Recall: 1.0 |
| - F1: 1.0 |
| - Accuracy: 1.0 |
| |
| ## 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: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - training_steps: 1000 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 8.33 | 100 | 0.3533 | 0.4147 | 0.3516 | 0.3805 | 0.8964 | |
| | No log | 16.67 | 200 | 0.0993 | 0.884 | 0.8633 | 0.8735 | 0.9782 | |
| | No log | 25.0 | 300 | 0.0338 | 0.9882 | 0.9805 | 0.9843 | 0.9977 | |
| | No log | 33.33 | 400 | 0.0173 | 0.9961 | 0.9922 | 0.9941 | 0.9992 | |
| | 0.238 | 41.67 | 500 | 0.0109 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.238 | 50.0 | 600 | 0.0081 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.238 | 58.33 | 700 | 0.0068 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.238 | 66.67 | 800 | 0.0061 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.238 | 75.0 | 900 | 0.0057 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0136 | 83.33 | 1000 | 0.0056 | 1.0 | 1.0 | 1.0 | 1.0 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.2 |
| |
