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--- |
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license: cc-by-nc-sa-4.0 |
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base_model: microsoft/layoutlmv3-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: layoutmlv3_thursday_oct4_v7 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# layoutmlv3_thursday_oct4_v7 |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2861 |
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- Precision: 0.8352 |
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- Recall: 0.7894 |
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- F1: 0.8116 |
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- Accuracy: 0.9586 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.12 | 100 | 0.2568 | 0.8574 | 0.7770 | 0.8152 | 0.9586 | |
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| No log | 2.25 | 200 | 0.2653 | 0.8268 | 0.7858 | 0.8058 | 0.9581 | |
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| No log | 3.37 | 300 | 0.2728 | 0.7982 | 0.7770 | 0.7874 | 0.9565 | |
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| No log | 4.49 | 400 | 0.2626 | 0.8569 | 0.7735 | 0.8130 | 0.9589 | |
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| 0.114 | 5.62 | 500 | 0.2861 | 0.8352 | 0.7894 | 0.8116 | 0.9586 | |
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| 0.114 | 6.74 | 600 | 0.2978 | 0.8205 | 0.7929 | 0.8065 | 0.9582 | |
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| 0.114 | 7.87 | 700 | 0.2942 | 0.8256 | 0.7876 | 0.8062 | 0.9584 | |
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| 0.114 | 8.99 | 800 | 0.2910 | 0.8420 | 0.7735 | 0.8063 | 0.9579 | |
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| 0.114 | 10.11 | 900 | 0.3028 | 0.8346 | 0.7770 | 0.8048 | 0.9574 | |
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| 0.0846 | 11.24 | 1000 | 0.2989 | 0.8318 | 0.7876 | 0.8091 | 0.9581 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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