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alitavanaali
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music_layoutlmv3_model

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layoutlmv3
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update model card README.md

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@@ -24,16 +24,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.9693877551020408
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  - name: Recall
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  type: recall
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- value: 0.9693877551020408
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  - name: F1
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  type: f1
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- value: 0.9693877551020408
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  - name: Accuracy
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  type: accuracy
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- value: 0.9987365761212887
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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
@@ -43,11 +43,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the sroie dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0085
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- - Precision: 0.9694
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- - Recall: 0.9694
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- - F1: 0.9694
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- - Accuracy: 0.9987
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  ## Model description
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@@ -78,21 +78,21 @@ 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 | 12.5 | 100 | 0.0094 | 0.9694 | 0.9694 | 0.9694 | 0.9987 |
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- | No log | 25.0 | 200 | 0.0076 | 0.9694 | 0.9694 | 0.9694 | 0.9987 |
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- | No log | 37.5 | 300 | 0.0079 | 0.9694 | 0.9694 | 0.9694 | 0.9987 |
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- | No log | 50.0 | 400 | 0.0079 | 0.9694 | 0.9694 | 0.9694 | 0.9987 |
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- | 0.0412 | 62.5 | 500 | 0.0080 | 0.9694 | 0.9694 | 0.9694 | 0.9987 |
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- | 0.0412 | 75.0 | 600 | 0.0083 | 0.9694 | 0.9694 | 0.9694 | 0.9987 |
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- | 0.0412 | 87.5 | 700 | 0.0083 | 0.9694 | 0.9694 | 0.9694 | 0.9987 |
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- | 0.0412 | 100.0 | 800 | 0.0084 | 0.9694 | 0.9694 | 0.9694 | 0.9987 |
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- | 0.0412 | 112.5 | 900 | 0.0084 | 0.9694 | 0.9694 | 0.9694 | 0.9987 |
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- | 0.0005 | 125.0 | 1000 | 0.0085 | 0.9694 | 0.9694 | 0.9694 | 0.9987 |
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  ### Framework versions
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- - Transformers 4.27.0.dev0
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  - Pytorch 1.13.1+cu116
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  - Datasets 2.2.2
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  - Tokenizers 0.13.2
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.9626865671641791
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  - name: Recall
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  type: recall
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+ value: 0.9772727272727273
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  - name: F1
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  type: f1
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+ value: 0.9699248120300752
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9990407673860912
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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 [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the sroie dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0083
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+ - Precision: 0.9627
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+ - Recall: 0.9773
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+ - F1: 0.9699
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+ - Accuracy: 0.9990
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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 | 8.33 | 100 | 0.0191 | 0.9338 | 0.9621 | 0.9478 | 0.9981 |
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+ | No log | 16.67 | 200 | 0.0120 | 0.9412 | 0.9697 | 0.9552 | 0.9981 |
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+ | No log | 25.0 | 300 | 0.0125 | 0.9412 | 0.9697 | 0.9552 | 0.9981 |
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+ | No log | 33.33 | 400 | 0.0101 | 0.9412 | 0.9697 | 0.9552 | 0.9981 |
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+ | 0.0527 | 41.67 | 500 | 0.0121 | 0.9412 | 0.9697 | 0.9552 | 0.9981 |
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+ | 0.0527 | 50.0 | 600 | 0.0083 | 0.9627 | 0.9773 | 0.9699 | 0.9990 |
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+ | 0.0527 | 58.33 | 700 | 0.0082 | 0.9627 | 0.9773 | 0.9699 | 0.9990 |
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+ | 0.0527 | 66.67 | 800 | 0.0082 | 0.9627 | 0.9773 | 0.9699 | 0.9990 |
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+ | 0.0527 | 75.0 | 900 | 0.0083 | 0.9627 | 0.9773 | 0.9699 | 0.9990 |
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+ | 0.0006 | 83.33 | 1000 | 0.0083 | 0.9627 | 0.9773 | 0.9699 | 0.9990 |
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  ### Framework versions
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+ - Transformers 4.28.0.dev0
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  - Pytorch 1.13.1+cu116
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  - Datasets 2.2.2
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  - Tokenizers 0.13.2