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P.E.R.S_WILD

Token Classification
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layoutlmv3
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P.E.R.S_WILD

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  1. README.md +129 -0
  2. model.safetensors +1 -1
  3. runs/Jun18_16-53-03_BRONZONG/events.out.tfevents.1718727290.BRONZONG.10453.1 +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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+ datasets:
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+ - wild
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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: P.E.R.S_WILD
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: wild
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+ type: wild
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+ config: WildReceipt
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+ split: test
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+ args: WildReceipt
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.8621359223300971
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+ - name: Recall
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+ type: recall
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+ value: 0.8556090846524432
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+ - name: F1
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+ type: f1
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+ value: 0.8588601036269431
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9165934548649243
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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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+ # P.E.R.S_WILD
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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 the wild dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3319
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+ - Precision: 0.8621
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+ - Recall: 0.8556
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+ - F1: 0.8589
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+ - Accuracy: 0.9166
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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: 1
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+ - eval_batch_size: 1
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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 | 0.0789 | 100 | 1.7570 | 0.4014 | 0.0807 | 0.1343 | 0.5202 |
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+ | No log | 0.1579 | 200 | 1.2158 | 0.5444 | 0.3515 | 0.4272 | 0.6895 |
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+ | No log | 0.2368 | 300 | 0.9862 | 0.6676 | 0.4763 | 0.5559 | 0.7534 |
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+ | No log | 0.3157 | 400 | 0.8539 | 0.6740 | 0.5898 | 0.6291 | 0.7883 |
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+ | 1.3192 | 0.3946 | 500 | 0.7150 | 0.7489 | 0.6325 | 0.6858 | 0.8208 |
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+ | 1.3192 | 0.4736 | 600 | 0.6731 | 0.7487 | 0.6716 | 0.7080 | 0.8288 |
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+ | 1.3192 | 0.5525 | 700 | 0.6345 | 0.7588 | 0.6848 | 0.7199 | 0.8357 |
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+ | 1.3192 | 0.6314 | 800 | 0.5903 | 0.7671 | 0.7181 | 0.7418 | 0.8472 |
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+ | 1.3192 | 0.7103 | 900 | 0.5273 | 0.7743 | 0.7718 | 0.7731 | 0.8690 |
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+ | 0.7013 | 0.7893 | 1000 | 0.4923 | 0.7939 | 0.7555 | 0.7742 | 0.8689 |
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+ | 0.7013 | 0.8682 | 1100 | 0.4811 | 0.8147 | 0.7619 | 0.7874 | 0.8742 |
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+ | 0.7013 | 0.9471 | 1200 | 0.4694 | 0.8006 | 0.7985 | 0.7995 | 0.8812 |
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+ | 0.7013 | 1.0260 | 1300 | 0.4429 | 0.8246 | 0.8058 | 0.8151 | 0.8866 |
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+ | 0.7013 | 1.1050 | 1400 | 0.4302 | 0.8135 | 0.8051 | 0.8093 | 0.8863 |
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+ | 0.4844 | 1.1839 | 1500 | 0.4364 | 0.7964 | 0.8245 | 0.8102 | 0.8875 |
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+ | 0.4844 | 1.2628 | 1600 | 0.4445 | 0.8012 | 0.8299 | 0.8153 | 0.8857 |
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+ | 0.4844 | 1.3418 | 1700 | 0.4021 | 0.8175 | 0.8244 | 0.8209 | 0.8918 |
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+ | 0.4844 | 1.4207 | 1800 | 0.3886 | 0.8290 | 0.8193 | 0.8241 | 0.8958 |
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+ | 0.4844 | 1.4996 | 1900 | 0.3708 | 0.8271 | 0.8372 | 0.8321 | 0.9000 |
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+ | 0.411 | 1.5785 | 2000 | 0.3910 | 0.8356 | 0.8310 | 0.8333 | 0.8996 |
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+ | 0.411 | 1.6575 | 2100 | 0.3550 | 0.8419 | 0.8399 | 0.8409 | 0.9069 |
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+ | 0.411 | 1.7364 | 2200 | 0.3499 | 0.8374 | 0.8451 | 0.8413 | 0.9066 |
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+ | 0.411 | 1.8153 | 2300 | 0.3532 | 0.8301 | 0.8512 | 0.8405 | 0.9050 |
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+ | 0.411 | 1.8942 | 2400 | 0.3763 | 0.8285 | 0.8471 | 0.8377 | 0.9018 |
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+ | 0.3641 | 1.9732 | 2500 | 0.3508 | 0.8529 | 0.8410 | 0.8469 | 0.9067 |
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+ | 0.3641 | 2.0521 | 2600 | 0.3616 | 0.8507 | 0.8384 | 0.8445 | 0.9083 |
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+ | 0.3641 | 2.1310 | 2700 | 0.3705 | 0.8485 | 0.8511 | 0.8498 | 0.9086 |
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+ | 0.3641 | 2.2099 | 2800 | 0.3527 | 0.8436 | 0.8562 | 0.8498 | 0.9118 |
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+ | 0.3641 | 2.2889 | 2900 | 0.3383 | 0.8658 | 0.8475 | 0.8566 | 0.9135 |
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+ | 0.2824 | 2.3678 | 3000 | 0.3395 | 0.8527 | 0.8523 | 0.8525 | 0.9124 |
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+ | 0.2824 | 2.4467 | 3100 | 0.3364 | 0.8622 | 0.8478 | 0.8549 | 0.9140 |
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+ | 0.2824 | 2.5257 | 3200 | 0.3383 | 0.8431 | 0.8619 | 0.8524 | 0.9125 |
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+ | 0.2824 | 2.6046 | 3300 | 0.3377 | 0.8530 | 0.8586 | 0.8558 | 0.9132 |
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+ | 0.2824 | 2.6835 | 3400 | 0.3389 | 0.8481 | 0.8629 | 0.8554 | 0.9135 |
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+ | 0.2928 | 2.7624 | 3500 | 0.3319 | 0.8621 | 0.8556 | 0.8589 | 0.9166 |
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+ | 0.2928 | 2.8414 | 3600 | 0.3341 | 0.8555 | 0.8575 | 0.8565 | 0.9153 |
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+ | 0.2928 | 2.9203 | 3700 | 0.3341 | 0.8536 | 0.8603 | 0.8569 | 0.9153 |
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+ | 0.2928 | 2.9992 | 3800 | 0.3305 | 0.8556 | 0.8636 | 0.8596 | 0.9167 |
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+ | 0.2928 | 3.0781 | 3900 | 0.3313 | 0.8579 | 0.8613 | 0.8596 | 0.9166 |
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+ | 0.2487 | 3.1571 | 4000 | 0.3326 | 0.8550 | 0.8604 | 0.8577 | 0.9160 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.0.dev0
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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