| ---
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| library_name: transformers
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| license: cc-by-nc-sa-4.0
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| base_model: impira/layoutlm-invoices
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| tags:
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| - generated_from_trainer
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| model-index:
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| - name: layoutlm-finetuned
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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
|
| should probably proofread and complete it, then remove this comment. -->
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|
|
| # layoutlm-finetuned
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|
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| This model is a fine-tuned version of [impira/layoutlm-invoices](https://huggingface.co/impira/layoutlm-invoices) on an unknown dataset.
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| It achieves the following results on the evaluation set:
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| - Loss: 0.0064
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|
|
| ## Model description
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| More information needed
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|
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| ## Intended uses & limitations
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| More information needed
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|
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| ## Training and evaluation data
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| More information needed
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|
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| ## Training procedure
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|
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| ### Training hyperparameters
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| The following hyperparameters were used during training:
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| - learning_rate: 3e-05
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| - train_batch_size: 4
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| - eval_batch_size: 4
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| - seed: 42
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| - gradient_accumulation_steps: 4
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| - total_train_batch_size: 16
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| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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| - lr_scheduler_type: linear
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| - lr_scheduler_warmup_steps: 100
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| - num_epochs: 10
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| - mixed_precision_training: Native AMP
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|
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| ### Training results
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|
| | Training Loss | Epoch | Step | Validation Loss |
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| |:-------------:|:------:|:----:|:---------------:|
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| | 0.0837 | 0.2116 | 100 | 0.0147 |
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| | 0.0603 | 0.4233 | 200 | 0.0101 |
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| | 0.0396 | 0.6349 | 300 | 0.0093 |
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| | 0.0442 | 0.8466 | 400 | 0.0086 |
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| | 0.0287 | 1.0571 | 500 | 0.0073 |
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| | 0.0396 | 1.2688 | 600 | 0.0084 |
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| | 0.0179 | 1.4804 | 700 | 0.0080 |
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| | 0.0391 | 1.6921 | 800 | 0.0069 |
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| | 0.0261 | 1.9037 | 900 | 0.0064 |
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| | 0.0146 | 2.1143 | 1000 | 0.0068 |
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| | 0.0192 | 2.3259 | 1100 | 0.0089 |
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| | 0.0233 | 2.5376 | 1200 | 0.0070 |
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| | 0.0129 | 2.7492 | 1300 | 0.0072 |
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| | 0.0173 | 2.9608 | 1400 | 0.0068 |
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| | 0.0217 | 3.1714 | 1500 | 0.0076 |
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| | 0.0198 | 3.3831 | 1600 | 0.0066 |
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| | 0.0163 | 3.5947 | 1700 | 0.0068 |
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| | 0.0142 | 3.8063 | 1800 | 0.0078 |
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| | 0.0144 | 4.0169 | 1900 | 0.0065 |
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| | 0.0143 | 4.2286 | 2000 | 0.0065 |
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| | 0.0125 | 4.4402 | 2100 | 0.0071 |
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| | 0.0108 | 4.6519 | 2200 | 0.0077 |
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| | 0.0138 | 4.8635 | 2300 | 0.0071 |
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| | 0.0146 | 5.0741 | 2400 | 0.0076 |
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| | 0.0135 | 5.2857 | 2500 | 0.0084 |
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| | 0.0213 | 5.4974 | 2600 | 0.0081 |
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| | 0.0117 | 5.7090 | 2700 | 0.0083 |
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| | 0.0181 | 5.9206 | 2800 | 0.0092 |
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| | 0.0124 | 6.1312 | 2900 | 0.0090 |
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| | 0.0102 | 6.3429 | 3000 | 0.0090 |
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| | 0.0110 | 6.5545 | 3100 | 0.0081 |
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| | 0.0100 | 6.7661 | 3200 | 0.0089 |
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| | 0.0111 | 6.9778 | 3300 | 0.0106 |
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| | 0.0127 | 7.1884 | 3400 | 0.0107 |
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| | 0.0075 | 7.4 | 3500 | 0.0106 |
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| | 0.0155 | 7.6116 | 3600 | 0.0104 |
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| | 0.0114 | 7.8233 | 3700 | 0.0104 |
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| | 0.0084 | 8.0339 | 3800 | 0.0100 |
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| | 0.0075 | 8.2455 | 3900 | 0.0112 |
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| | 0.0095 | 8.4571 | 4000 | 0.0115 |
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| | 0.0117 | 8.6688 | 4100 | 0.0115 |
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| | 0.0083 | 8.8804 | 4200 | 0.0118 |
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| | 0.0060 | 9.0910 | 4300 | 0.0118 |
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| | 0.0049 | 9.3026 | 4400 | 0.0130 |
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| | 0.0082 | 9.5143 | 4500 | 0.0129 |
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| | 0.0083 | 9.7259 | 4600 | 0.0131 |
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| | 0.0076 | 9.9376 | 4700 | 0.0130 |
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| | 0.0062 | 10.0 | 4730 | 0.0130 |
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| ### Framework versions
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|
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| - Transformers 5.11.0
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| - Pytorch 2.6.0+cu124
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| - Datasets 5.0.0
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| - Tokenizers 0.22.2
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|
