mp-02 commited on
Commit
30cea16
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verified ·
1 Parent(s): 6acc469

End of training

Browse files
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: 0.9036656236030398
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  - name: Recall
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  type: recall
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- value: 0.9578298981284056
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  - name: F1
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  type: f1
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- value: 0.9299597469810236
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  - name: Accuracy
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  type: accuracy
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- value: 0.9736783204261605
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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: 0.0967
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- - Precision: 0.9037
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- - Recall: 0.9578
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- - F1: 0.9300
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- - Accuracy: 0.9737
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  ## Model description
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@@ -76,18 +76,15 @@ 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 | 0.7937 | 100 | 0.4387 | 0.6226 | 0.5785 | 0.5998 | 0.9037 |
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- | No log | 1.5873 | 200 | 0.2236 | 0.8925 | 0.8439 | 0.8675 | 0.9562 |
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- | No log | 2.3810 | 300 | 0.1342 | 0.9127 | 0.8965 | 0.9045 | 0.9692 |
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- | No log | 3.1746 | 400 | 0.1054 | 0.9119 | 0.9273 | 0.9195 | 0.9735 |
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- | 0.6635 | 3.9683 | 500 | 0.1341 | 0.8555 | 0.9495 | 0.9001 | 0.9630 |
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- | 0.6635 | 4.7619 | 600 | 0.1060 | 0.9059 | 0.9493 | 0.9271 | 0.9739 |
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- | 0.6635 | 5.5556 | 700 | 0.1066 | 0.9080 | 0.9420 | 0.9247 | 0.9738 |
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- | 0.6635 | 6.3492 | 800 | 0.1008 | 0.9078 | 0.9564 | 0.9315 | 0.9746 |
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- | 0.6635 | 7.1429 | 900 | 0.0988 | 0.9086 | 0.9517 | 0.9296 | 0.9738 |
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- | 0.0995 | 7.9365 | 1000 | 0.0967 | 0.9037 | 0.9578 | 0.9300 | 0.9737 |
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- | 0.0995 | 8.7302 | 1100 | 0.1224 | 0.8777 | 0.9642 | 0.9189 | 0.9690 |
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- | 0.0995 | 9.5238 | 1200 | 0.1263 | 0.8879 | 0.9536 | 0.9196 | 0.9694 |
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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: 0.9129400570884871
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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
 
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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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  | 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
all_results.json CHANGED
@@ -1,10 +1,10 @@
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- "predict_steps_per_second": 0.922
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  }
 
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predict_results.json CHANGED
@@ -1,10 +1,10 @@
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  }
 
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+ "predict_steps_per_second": 0.914
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  }
predictions.txt CHANGED
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