mp-02 commited on
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End of training

Browse files
README.md CHANGED
@@ -11,7 +11,7 @@ metrics:
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  - f1
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  - accuracy
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  model-index:
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- - name: layoutlmv3-finetuned-cord-sroie
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  results:
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  - task:
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  name: Token Classification
@@ -22,30 +22,30 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.9539473684210527
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  - name: Recall
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  type: recall
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- value: 0.9618573797678275
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  - name: F1
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  type: f1
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- value: 0.9578860445912468
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  - name: Accuracy
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  type: accuracy
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- value: 0.9852276288106003
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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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- # layoutlmv3-finetuned-cord-sroie
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  This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the mp-02/cord-sroie dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0744
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  - Precision: 0.9539
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- - Recall: 0.9619
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- - F1: 0.9579
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- - Accuracy: 0.9852
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  ## Model description
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@@ -64,28 +64,40 @@ More information needed
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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: 10
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- - eval_batch_size: 10
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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: 2500
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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 | 1.7483 | 250 | 0.2724 | 0.7860 | 0.7768 | 0.7814 | 0.9414 |
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- | 0.7002 | 3.4965 | 500 | 0.1376 | 0.9001 | 0.9325 | 0.9160 | 0.9696 |
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- | 0.7002 | 5.2448 | 750 | 0.0983 | 0.9281 | 0.9417 | 0.9349 | 0.9781 |
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- | 0.176 | 6.9930 | 1000 | 0.0806 | 0.9411 | 0.9429 | 0.9420 | 0.9817 |
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- | 0.176 | 8.7413 | 1250 | 0.0779 | 0.9482 | 0.9462 | 0.9472 | 0.9824 |
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- | 0.0951 | 10.4895 | 1500 | 0.0740 | 0.9493 | 0.9581 | 0.9537 | 0.9844 |
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- | 0.0951 | 12.2378 | 1750 | 0.0744 | 0.9515 | 0.9614 | 0.9564 | 0.9848 |
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- | 0.0631 | 13.9860 | 2000 | 0.0740 | 0.9512 | 0.9607 | 0.9559 | 0.9846 |
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- | 0.0631 | 15.7343 | 2250 | 0.0756 | 0.9522 | 0.9588 | 0.9555 | 0.9846 |
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- | 0.0496 | 17.4825 | 2500 | 0.0744 | 0.9539 | 0.9619 | 0.9579 | 0.9852 |
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  - f1
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  - accuracy
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  model-index:
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+ - name: layoutlmv3-base-cord-sroie
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  results:
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  - task:
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  name: Token Classification
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.9539082917557614
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  - name: Recall
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  type: recall
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+ value: 0.951196398957593
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  - name: F1
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  type: f1
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+ value: 0.9525504151838672
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9836608621693004
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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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+ # layoutlmv3-base-cord-sroie
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  This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the mp-02/cord-sroie dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0748
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  - Precision: 0.9539
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+ - Recall: 0.9512
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+ - F1: 0.9526
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+ - Accuracy: 0.9837
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 6e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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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  ### 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 | 0.5556 | 50 | 0.5599 | 0.8723 | 0.5451 | 0.6709 | 0.8791 |
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+ | No log | 1.1111 | 100 | 0.4348 | 0.9023 | 0.6408 | 0.7494 | 0.8977 |
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+ | No log | 1.6667 | 150 | 0.2920 | 0.8816 | 0.8024 | 0.8401 | 0.9298 |
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+ | No log | 2.2222 | 200 | 0.2370 | 0.8846 | 0.8448 | 0.8643 | 0.9416 |
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+ | No log | 2.7778 | 250 | 0.1776 | 0.8491 | 0.8676 | 0.8582 | 0.9615 |
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+ | No log | 3.3333 | 300 | 0.1181 | 0.8935 | 0.9282 | 0.9105 | 0.9735 |
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+ | No log | 3.8889 | 350 | 0.0779 | 0.9355 | 0.9382 | 0.9368 | 0.9806 |
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+ | No log | 4.4444 | 400 | 0.0785 | 0.9444 | 0.9505 | 0.9475 | 0.9831 |
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+ | No log | 5.0 | 450 | 0.0675 | 0.9536 | 0.9552 | 0.9544 | 0.9848 |
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+ | 0.4435 | 5.5556 | 500 | 0.0756 | 0.9508 | 0.9469 | 0.9488 | 0.9829 |
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+ | 0.4435 | 6.1111 | 550 | 0.0708 | 0.9546 | 0.9555 | 0.9550 | 0.9847 |
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+ | 0.4435 | 6.6667 | 600 | 0.0707 | 0.9576 | 0.9472 | 0.9524 | 0.9841 |
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+ | 0.4435 | 7.2222 | 650 | 0.0630 | 0.9577 | 0.9552 | 0.9565 | 0.9854 |
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+ | 0.4435 | 7.7778 | 700 | 0.0679 | 0.9548 | 0.9614 | 0.9581 | 0.9860 |
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+ | 0.4435 | 8.3333 | 750 | 0.0665 | 0.9505 | 0.9642 | 0.9573 | 0.9858 |
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+ | 0.4435 | 8.8889 | 800 | 0.0687 | 0.9480 | 0.9628 | 0.9553 | 0.9850 |
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+ | 0.4435 | 9.4444 | 850 | 0.0730 | 0.9577 | 0.9555 | 0.9566 | 0.9850 |
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+ | 0.4435 | 10.0 | 900 | 0.0905 | 0.9634 | 0.9346 | 0.9488 | 0.9816 |
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+ | 0.4435 | 10.5556 | 950 | 0.0755 | 0.9523 | 0.9611 | 0.9567 | 0.9851 |
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+ | 0.0363 | 11.1111 | 1000 | 0.0748 | 0.9539 | 0.9512 | 0.9526 | 0.9837 |
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+ | 0.0363 | 11.6667 | 1050 | 0.0768 | 0.9531 | 0.9583 | 0.9557 | 0.9844 |
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+ | 0.0363 | 12.2222 | 1100 | 0.0759 | 0.9562 | 0.9611 | 0.9586 | 0.9855 |
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  ### Framework versions
all_results.json CHANGED
@@ -1,10 +1,10 @@
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  {
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- "predict_samples_per_second": 10.996,
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- "predict_steps_per_second": 1.128
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  }
 
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+ "predict_steps_per_second": 0.725
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  }
predict_results.json CHANGED
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- "predict_runtime": 24.8279,
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- "predict_samples_per_second": 10.996,
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- "predict_steps_per_second": 1.128
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  }
 
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+ "predict_runtime": 24.8356,
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+ "predict_samples_per_second": 10.992,
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+ "predict_steps_per_second": 0.725
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  }
predictions.txt CHANGED
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