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layoutlmv3-wildreceipt

Token Classification
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layoutlmv3
generated_from_trainer
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  1. README.md +105 -0
  2. model.safetensors +1 -1
  3. runs/Mar28_10-41-50_c974346ac33f/events.out.tfevents.1711630214.c974346ac33f.187.1 +3 -0
README.md ADDED
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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: layoutlmv3-wildreceipt
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+ results: []
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+ ---
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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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+
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+ # layoutlmv3-wildreceipt
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+
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+ This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3399
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+ - Precision: 0.8693
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+ - Recall: 0.8761
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+ - F1: 0.8727
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+ - Accuracy: 0.9225
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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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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+
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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: 4
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+ - eval_batch_size: 4
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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: 4000
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 0.4 | 100 | 1.3257 | 0.6259 | 0.2897 | 0.3961 | 0.6677 |
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+ | No log | 0.8 | 200 | 0.8512 | 0.6479 | 0.5297 | 0.5829 | 0.7870 |
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+ | No log | 1.2 | 300 | 0.6603 | 0.7311 | 0.6472 | 0.6866 | 0.8302 |
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+ | No log | 1.6 | 400 | 0.5604 | 0.7580 | 0.7144 | 0.7355 | 0.8515 |
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+ | 1.0344 | 2.0 | 500 | 0.4834 | 0.7920 | 0.7515 | 0.7712 | 0.8711 |
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+ | 1.0344 | 2.4 | 600 | 0.4352 | 0.8070 | 0.7792 | 0.7929 | 0.8812 |
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+ | 1.0344 | 2.8 | 700 | 0.4045 | 0.8146 | 0.8149 | 0.8148 | 0.8925 |
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+ | 1.0344 | 3.2 | 800 | 0.4051 | 0.8067 | 0.8208 | 0.8137 | 0.8897 |
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+ | 1.0344 | 3.6 | 900 | 0.3774 | 0.8211 | 0.8328 | 0.8269 | 0.8977 |
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+ | 0.3942 | 4.0 | 1000 | 0.3556 | 0.8355 | 0.8340 | 0.8347 | 0.9025 |
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+ | 0.3942 | 4.4 | 1100 | 0.3703 | 0.8211 | 0.8496 | 0.8351 | 0.9001 |
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+ | 0.3942 | 4.8 | 1200 | 0.3430 | 0.8367 | 0.8486 | 0.8426 | 0.9057 |
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+ | 0.3942 | 5.2 | 1300 | 0.3492 | 0.8349 | 0.8469 | 0.8409 | 0.9051 |
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+ | 0.3942 | 5.6 | 1400 | 0.3259 | 0.8551 | 0.8498 | 0.8525 | 0.9108 |
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+ | 0.2561 | 6.0 | 1500 | 0.3276 | 0.8422 | 0.8610 | 0.8515 | 0.9113 |
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+ | 0.2561 | 6.4 | 1600 | 0.3307 | 0.8546 | 0.8497 | 0.8522 | 0.9110 |
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+ | 0.2561 | 6.8 | 1700 | 0.3180 | 0.8527 | 0.8559 | 0.8543 | 0.9136 |
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+ | 0.2561 | 7.2 | 1800 | 0.3239 | 0.8525 | 0.8593 | 0.8559 | 0.9135 |
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+ | 0.2561 | 7.6 | 1900 | 0.3322 | 0.8499 | 0.8703 | 0.8600 | 0.9145 |
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+ | 0.1866 | 8.0 | 2000 | 0.3265 | 0.8465 | 0.8681 | 0.8572 | 0.9131 |
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+ | 0.1866 | 8.4 | 2100 | 0.3248 | 0.8588 | 0.8618 | 0.8603 | 0.9170 |
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+ | 0.1866 | 8.8 | 2200 | 0.3269 | 0.8579 | 0.8629 | 0.8604 | 0.9162 |
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+ | 0.1866 | 9.2 | 2300 | 0.3273 | 0.8656 | 0.8663 | 0.8660 | 0.9195 |
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+ | 0.1866 | 9.6 | 2400 | 0.3312 | 0.8593 | 0.8702 | 0.8647 | 0.9187 |
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+ | 0.1439 | 10.0 | 2500 | 0.3200 | 0.8639 | 0.8703 | 0.8671 | 0.9209 |
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+ | 0.1439 | 10.4 | 2600 | 0.3367 | 0.8540 | 0.8761 | 0.8649 | 0.9183 |
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+ | 0.1439 | 10.8 | 2700 | 0.3370 | 0.8614 | 0.8699 | 0.8656 | 0.9191 |
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+ | 0.1439 | 11.2 | 2800 | 0.3294 | 0.8735 | 0.8690 | 0.8712 | 0.9221 |
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+ | 0.1439 | 11.6 | 2900 | 0.3405 | 0.8653 | 0.8734 | 0.8693 | 0.9205 |
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+ | 0.1186 | 12.0 | 3000 | 0.3334 | 0.8629 | 0.8767 | 0.8697 | 0.9210 |
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+ | 0.1186 | 12.4 | 3100 | 0.3376 | 0.8653 | 0.8747 | 0.8700 | 0.9218 |
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+ | 0.1186 | 12.8 | 3200 | 0.3362 | 0.8663 | 0.8752 | 0.8707 | 0.9209 |
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+ | 0.1186 | 13.2 | 3300 | 0.3317 | 0.8729 | 0.8719 | 0.8724 | 0.9225 |
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+ | 0.1186 | 13.6 | 3400 | 0.3408 | 0.8706 | 0.8714 | 0.8710 | 0.9213 |
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+ | 0.0997 | 14.0 | 3500 | 0.3399 | 0.8693 | 0.8761 | 0.8727 | 0.9225 |
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+ | 0.0997 | 14.4 | 3600 | 0.3445 | 0.8623 | 0.8767 | 0.8694 | 0.9208 |
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+ | 0.0997 | 14.8 | 3700 | 0.3403 | 0.8673 | 0.8775 | 0.8724 | 0.9225 |
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+ | 0.0997 | 15.2 | 3800 | 0.3492 | 0.8652 | 0.8763 | 0.8707 | 0.9209 |
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+ | 0.0997 | 15.6 | 3900 | 0.3442 | 0.8692 | 0.8760 | 0.8726 | 0.9228 |
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+ | 0.0891 | 16.0 | 4000 | 0.3441 | 0.8672 | 0.8767 | 0.8719 | 0.9225 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0.dev0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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