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layoutlmv3-for-complete-receipt-understanding

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layoutlmv3-for-complete-receipt-understanding

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  1. README.md +26 -12
  2. model.safetensors +1 -1
  3. runs/Oct13_21-00-23_c18c0c7f929a/events.out.tfevents.1728853588.c18c0c7f929a.30747.3 +3 -0
  4. runs/Oct13_21-35-30_c18c0c7f929a/events.out.tfevents.1728855337.c18c0c7f929a.30747.4 +3 -0
  5. runs/Oct13_21-35-30_c18c0c7f929a/events.out.tfevents.1728856649.c18c0c7f929a.30747.5 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [NLPmonster/layoutlmv3-for-receipt-understanding](https://huggingface.co/NLPmonster/layoutlmv3-for-receipt-understanding) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0019
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- - Precision: 1.0
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- - Recall: 1.0
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- - F1: 1.0
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- - Accuracy: 1.0
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  ## Model description
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@@ -50,18 +50,32 @@ The following hyperparameters were used during training:
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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: 300
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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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- | 1.0503 | 0.4425 | 50 | 0.0558 | 0.8777 | 0.9457 | 0.9104 | 0.9921 |
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- | 0.0565 | 0.8850 | 100 | 0.0100 | 0.9697 | 0.9922 | 0.9808 | 0.9979 |
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- | 0.0237 | 1.3274 | 150 | 0.0048 | 0.9771 | 0.9922 | 0.9846 | 0.9989 |
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- | 0.0278 | 1.7699 | 200 | 0.0025 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0118 | 2.2124 | 250 | 0.0020 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0051 | 2.6549 | 300 | 0.0019 | 1.0 | 1.0 | 1.0 | 1.0 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [NLPmonster/layoutlmv3-for-receipt-understanding](https://huggingface.co/NLPmonster/layoutlmv3-for-receipt-understanding) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5246
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+ - Precision: 0.7795
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+ - Recall: 0.7867
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+ - F1: 0.7831
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+ - Accuracy: 0.8572
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  ## Model description
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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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+ | 0.2792 | 0.4425 | 50 | 0.5236 | 0.7608 | 0.7535 | 0.7571 | 0.8398 |
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+ | 0.3022 | 0.8850 | 100 | 0.5262 | 0.7709 | 0.7541 | 0.7624 | 0.8420 |
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+ | 0.2821 | 1.3274 | 150 | 0.5263 | 0.7704 | 0.7616 | 0.7660 | 0.8403 |
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+ | 0.2801 | 1.7699 | 200 | 0.5310 | 0.7645 | 0.7659 | 0.7652 | 0.8412 |
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+ | 0.2545 | 2.2124 | 250 | 0.5425 | 0.7606 | 0.7685 | 0.7645 | 0.8416 |
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+ | 0.2453 | 2.6549 | 300 | 0.5237 | 0.7624 | 0.7602 | 0.7613 | 0.8417 |
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+ | 0.2464 | 3.0973 | 350 | 0.5169 | 0.7699 | 0.7721 | 0.7710 | 0.8459 |
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+ | 0.2248 | 3.5398 | 400 | 0.5266 | 0.7666 | 0.7701 | 0.7683 | 0.8447 |
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+ | 0.2117 | 3.9823 | 450 | 0.5041 | 0.7754 | 0.7751 | 0.7753 | 0.8496 |
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+ | 0.1986 | 4.4248 | 500 | 0.5327 | 0.7673 | 0.7729 | 0.7701 | 0.8453 |
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+ | 0.1832 | 4.8673 | 550 | 0.5462 | 0.7658 | 0.7606 | 0.7632 | 0.8423 |
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+ | 0.1752 | 5.3097 | 600 | 0.5207 | 0.7738 | 0.7830 | 0.7783 | 0.8519 |
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+ | 0.1698 | 5.7522 | 650 | 0.5247 | 0.7737 | 0.7763 | 0.7750 | 0.8514 |
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+ | 0.1495 | 6.1947 | 700 | 0.5433 | 0.7702 | 0.7754 | 0.7727 | 0.8495 |
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+ | 0.1487 | 6.6372 | 750 | 0.5363 | 0.7731 | 0.7784 | 0.7757 | 0.8505 |
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+ | 0.1431 | 7.0796 | 800 | 0.5276 | 0.7792 | 0.7754 | 0.7773 | 0.8544 |
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+ | 0.1283 | 7.5221 | 850 | 0.5344 | 0.7752 | 0.7816 | 0.7784 | 0.8536 |
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+ | 0.1253 | 7.9646 | 900 | 0.5166 | 0.7887 | 0.7834 | 0.7861 | 0.8594 |
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+ | 0.1176 | 8.4071 | 950 | 0.5261 | 0.7794 | 0.7834 | 0.7814 | 0.8571 |
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+ | 0.1124 | 8.8496 | 1000 | 0.5246 | 0.7795 | 0.7867 | 0.7831 | 0.8572 |
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  ### Framework versions
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