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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_oct_7_v5 |
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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_oct_7_v5 |
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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: 0.1171 |
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- Precision: 0.8763 |
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- Recall: 0.9075 |
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- F1: 0.8916 |
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- Accuracy: 0.9821 |
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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 | 0.86 | 100 | 0.2961 | 0.8166 | 0.8559 | 0.8358 | 0.9372 | |
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| No log | 1.72 | 200 | 0.1481 | 0.8037 | 0.8594 | 0.8306 | 0.9674 | |
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| No log | 2.59 | 300 | 0.1191 | 0.8082 | 0.8772 | 0.8413 | 0.9753 | |
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| No log | 3.45 | 400 | 0.0892 | 0.8969 | 0.9128 | 0.9048 | 0.9844 | |
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| 0.29 | 4.31 | 500 | 0.1171 | 0.8763 | 0.9075 | 0.8916 | 0.9821 | |
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| 0.29 | 5.17 | 600 | 0.0994 | 0.8864 | 0.9021 | 0.8942 | 0.9818 | |
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| 0.29 | 6.03 | 700 | 0.0851 | 0.8901 | 0.8932 | 0.8917 | 0.9844 | |
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| 0.29 | 6.9 | 800 | 0.0957 | 0.8425 | 0.8950 | 0.8680 | 0.9814 | |
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| 0.29 | 7.76 | 900 | 0.0951 | 0.8735 | 0.8968 | 0.8850 | 0.9834 | |
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| 0.1351 | 8.62 | 1000 | 0.1005 | 0.8772 | 0.9021 | 0.8895 | 0.9840 | |
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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 0.14.1 |
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