renjithks
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layoutlmv3-er-ner

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renjithks commited on May 25, 2022

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@@ -18,11 +18,11 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [renjithks/layoutlmv3-cord-ner](https://huggingface.co/renjithks/layoutlmv3-cord-ner) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1905
-- Precision: 0.6189
-- Recall: 0.6591
-- F1: 0.6384
-- Accuracy: 0.9529
 ## Model description
@@ -53,16 +53,16 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 22   | 0.2818          | 0.3420    | 0.2801 | 0.3079 | 0.9064   |
-| No log        | 2.0   | 44   | 0.1898          | 0.5280    | 0.4540 | 0.4882 | 0.9380   |
-| No log        | 3.0   | 66   | 0.1729          | 0.5992    | 0.6153 | 0.6071 | 0.9479   |
-| No log        | 4.0   | 88   | 0.1880          | 0.6179    | 0.6040 | 0.6109 | 0.9457   |
-| No log        | 5.0   | 110  | 0.1845          | 0.5607    | 0.5941 | 0.5769 | 0.9451   |
-| No log        | 6.0   | 132  | 0.1869          | 0.6071    | 0.6294 | 0.6181 | 0.9501   |
-| No log        | 7.0   | 154  | 0.1838          | 0.6288    | 0.6492 | 0.6388 | 0.9517   |
-| No log        | 8.0   | 176  | 0.1928          | 0.5973    | 0.6167 | 0.6068 | 0.9503   |
-| No log        | 9.0   | 198  | 0.1899          | 0.6179    | 0.6634 | 0.6398 | 0.9521   |
-| No log        | 10.0  | 220  | 0.1905          | 0.6189    | 0.6591 | 0.6384 | 0.9529   |
 ### Framework versions

 This model is a fine-tuned version of [renjithks/layoutlmv3-cord-ner](https://huggingface.co/renjithks/layoutlmv3-cord-ner) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.1788
+- Precision: 0.6612
+- Recall: 0.6789
+- F1: 0.6699
+- Accuracy: 0.9549
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 22   | 0.3892          | 0.0       | 0.0    | 0.0    | 0.8793   |
+| No log        | 2.0   | 44   | 0.2854          | 0.3343    | 0.3352 | 0.3347 | 0.8956   |
+| No log        | 3.0   | 66   | 0.2085          | 0.5692    | 0.5233 | 0.5453 | 0.9388   |
+| No log        | 4.0   | 88   | 0.1785          | 0.5556    | 0.6153 | 0.5839 | 0.9426   |
+| No log        | 5.0   | 110  | 0.1853          | 0.5769    | 0.6365 | 0.6052 | 0.9455   |
+| No log        | 6.0   | 132  | 0.1593          | 0.6592    | 0.6676 | 0.6634 | 0.9539   |
+| No log        | 7.0   | 154  | 0.1684          | 0.6676    | 0.6506 | 0.6590 | 0.9529   |
+| No log        | 8.0   | 176  | 0.1759          | 0.6443    | 0.6506 | 0.6474 | 0.9537   |
+| No log        | 9.0   | 198  | 0.1740          | 0.6607    | 0.6832 | 0.6718 | 0.9555   |
+| No log        | 10.0  | 220  | 0.1788          | 0.6612    | 0.6789 | 0.6699 | 0.9549   |
 ### Framework versions