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layoutlmv3-base-cord-sroie

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End of training

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Files changed (6) hide show
  1. README.md +21 -18
  2. all_results.json +8 -8
  3. predict_results.json +8 -8
  4. predictions.txt +0 -0
  5. runs/Nov18_01-36-06_9aa9783f70bc/events.out.tfevents.1731893768.9aa9783f70bc.2068.0 +2 -2
  6. runs/Nov18_01-36-06_9aa9783f70bc/events.out.tfevents.1731896229.9aa9783f70bc.2068.1 +3 -0
README.md CHANGED
@@ -22,16 +22,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.9129400570884871
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  - name: Recall
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  type: recall
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- value: 0.9092632077706705
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  - name: F1
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  type: f1
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- value: 0.9110979228486646
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  - name: Accuracy
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  type: accuracy
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- value: 0.9692018443081606
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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
@@ -41,11 +41,11 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.1101
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- - Precision: 0.9129
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- - Recall: 0.9093
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- - F1: 0.9111
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- - Accuracy: 0.9692
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  ## Model description
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@@ -76,15 +76,18 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 0.7143 | 100 | 0.4587 | 0.5999 | 0.6098 | 0.6048 | 0.8921 |
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- | No log | 1.4286 | 200 | 0.2729 | 0.8217 | 0.8299 | 0.8258 | 0.9428 |
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- | No log | 2.1429 | 300 | 0.1556 | 0.9019 | 0.8998 | 0.9009 | 0.9678 |
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- | No log | 2.8571 | 400 | 0.1274 | 0.8712 | 0.9372 | 0.9030 | 0.9652 |
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- | 0.6303 | 3.5714 | 500 | 0.1101 | 0.9129 | 0.9093 | 0.9111 | 0.9692 |
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- | 0.6303 | 4.2857 | 600 | 0.0870 | 0.9131 | 0.9510 | 0.9316 | 0.9761 |
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- | 0.6303 | 5.0 | 700 | 0.0971 | 0.9089 | 0.9505 | 0.9292 | 0.9741 |
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- | 0.6303 | 5.7143 | 800 | 0.1198 | 0.8859 | 0.9384 | 0.9114 | 0.9682 |
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- | 0.6303 | 6.4286 | 900 | 0.1308 | 0.8930 | 0.9514 | 0.9213 | 0.9713 |
 
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.9105022831050228
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  - name: Recall
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  type: recall
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+ value: 0.9447998104714522
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  - name: F1
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  type: f1
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+ value: 0.9273340309266364
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9738126147097005
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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
 
41
 
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  This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the mp-02/cord-sroie dataset.
43
  It achieves the following results on the evaluation set:
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+ - Loss: 0.0936
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+ - Precision: 0.9105
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+ - Recall: 0.9448
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+ - F1: 0.9273
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+ - Accuracy: 0.9738
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 0.7937 | 100 | 0.4396 | 0.6271 | 0.6015 | 0.6140 | 0.9064 |
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+ | No log | 1.5873 | 200 | 0.2500 | 0.8669 | 0.8394 | 0.8529 | 0.9508 |
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+ | No log | 2.3810 | 300 | 0.1517 | 0.8682 | 0.9050 | 0.8862 | 0.9634 |
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+ | No log | 3.1746 | 400 | 0.1346 | 0.8694 | 0.9339 | 0.9005 | 0.9645 |
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+ | 0.6691 | 3.9683 | 500 | 0.0943 | 0.9369 | 0.9325 | 0.9347 | 0.9778 |
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+ | 0.6691 | 4.7619 | 600 | 0.0922 | 0.9049 | 0.9491 | 0.9265 | 0.9742 |
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+ | 0.6691 | 5.5556 | 700 | 0.1106 | 0.8913 | 0.9540 | 0.9216 | 0.9717 |
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+ | 0.6691 | 6.3492 | 800 | 0.0875 | 0.9091 | 0.9552 | 0.9316 | 0.9755 |
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+ | 0.6691 | 7.1429 | 900 | 0.0958 | 0.8977 | 0.9623 | 0.9289 | 0.9743 |
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+ | 0.1055 | 7.9365 | 1000 | 0.0936 | 0.9105 | 0.9448 | 0.9273 | 0.9738 |
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+ | 0.1055 | 8.7302 | 1100 | 0.1035 | 0.9289 | 0.9415 | 0.9352 | 0.9766 |
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+ | 0.1055 | 9.5238 | 1200 | 0.1115 | 0.9081 | 0.9507 | 0.9289 | 0.9739 |
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  ### Framework versions
all_results.json CHANGED
@@ -1,10 +1,10 @@
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  {
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- "predict_accuracy": 0.9747414660931637,
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- "predict_samples_per_second": 7.133,
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- "predict_steps_per_second": 0.914
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  }
 
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  {
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+ "predict_samples_per_second": 7.25,
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+ "predict_steps_per_second": 0.929
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  }
predict_results.json CHANGED
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  {
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- "predict_runtime": 38.2729,
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- "predict_samples_per_second": 7.133,
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- "predict_steps_per_second": 0.914
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  }
 
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  {
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+ "predict_loss": 0.0873132273554802,
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+ "predict_recall": 0.9528345724907064,
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+ "predict_runtime": 37.6564,
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+ "predict_samples_per_second": 7.25,
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+ "predict_steps_per_second": 0.929
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  }
predictions.txt CHANGED
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