mp-02/layoutlmv3-finetuned-funsd2

README.md

@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2991
-- Precision: 0.7279
-- Recall: 0.7091
-- F1: 0.7183
-- Accuracy: 0.9111
+- Loss: 0.6633
+- Precision: 0.9027
+- Recall: 0.9090
+- F1: 0.9058
+- Accuracy: 0.8500
 
 ## Model description
 
@@ -55,18 +55,18 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 0.9091  | 10   | 0.5192          | 0.5148    | 0.4871 | 0.5006 | 0.8322   |
-| No log        | 1.8182  | 20   | 0.3608          | 0.6485    | 0.6164 | 0.6320 | 0.8912   |
-| No log        | 2.7273  | 30   | 0.2978          | 0.6762    | 0.6616 | 0.6688 | 0.9027   |
-| No log        | 3.6364  | 40   | 0.2697          | 0.6768    | 0.6724 | 0.6746 | 0.8996   |
-| No log        | 4.5455  | 50   | 0.2737          | 0.6726    | 0.6509 | 0.6616 | 0.8989   |
-| No log        | 5.4545  | 60   | 0.2784          | 0.6667    | 0.6724 | 0.6695 | 0.8973   |
-| No log        | 6.3636  | 70   | 0.2536          | 0.7054    | 0.6810 | 0.6930 | 0.9096   |
-| No log        | 7.2727  | 80   | 0.2803          | 0.7100    | 0.7069 | 0.7084 | 0.9103   |
-| No log        | 8.1818  | 90   | 0.2924          | 0.7165    | 0.7026 | 0.7095 | 0.9057   |
-| No log        | 9.0909  | 100  | 0.2993          | 0.6801    | 0.6918 | 0.6859 | 0.9004   |
-| No log        | 10.0    | 110  | 0.3056          | 0.7013    | 0.6983 | 0.6998 | 0.9057   |
-| No log        | 10.9091 | 120  | 0.2991          | 0.7279    | 0.7091 | 0.7183 | 0.9111   |
+| No log        | 0.9091  | 10   | 0.9825          | 0.5685    | 0.6133 | 0.5901 | 0.6804   |
+| No log        | 1.8182  | 20   | 0.6492          | 0.7647    | 0.8215 | 0.7921 | 0.7781   |
+| No log        | 2.7273  | 30   | 0.5079          | 0.8037    | 0.8635 | 0.8326 | 0.8370   |
+| No log        | 3.6364  | 40   | 0.5371          | 0.8600    | 0.8924 | 0.8759 | 0.8428   |
+| No log        | 4.5455  | 50   | 0.5696          | 0.8753    | 0.8968 | 0.8859 | 0.8348   |
+| No log        | 5.4545  | 60   | 0.6309          | 0.8733    | 0.8863 | 0.8797 | 0.8272   |
+| No log        | 6.3636  | 70   | 0.6272          | 0.8878    | 0.9003 | 0.8940 | 0.8494   |
+| No log        | 7.2727  | 80   | 0.6168          | 0.9025    | 0.9151 | 0.9088 | 0.8688   |
+| No log        | 8.1818  | 90   | 0.6458          | 0.9094    | 0.9134 | 0.9114 | 0.8588   |
+| No log        | 9.0909  | 100  | 0.6830          | 0.8985    | 0.9064 | 0.9024 | 0.8490   |
+| No log        | 10.0    | 110  | 0.6325          | 0.9086    | 0.9221 | 0.9153 | 0.8502   |
+| No log        | 10.9091 | 120  | 0.6633          | 0.9027    | 0.9090 | 0.9058 | 0.8500   |
 
 
 ### Framework versions

all_results.json

@@ -1,10 +1,10 @@
 {
-    "predict_accuracy": 0.8892307692307693,
-    "predict_f1": 0.6833114323258869,
-    "predict_loss": 0.3853023946285248,
-    "predict_precision": 0.6718346253229974,
-    "predict_recall": 0.6951871657754011,
-    "predict_runtime": 1.5167,
-    "predict_samples_per_second": 11.868,
-    "predict_steps_per_second": 1.319
+    "predict_accuracy": 0.8218373936014088,
+    "predict_f1": 0.9038133181559477,
+    "predict_loss": 0.6888472437858582,
+    "predict_precision": 0.895152198421646,
+    "predict_recall": 0.9126436781609195,
+    "predict_runtime": 2.0596,
+    "predict_samples_per_second": 8.74,
+    "predict_steps_per_second": 0.971
 }

predict_results.json

@@ -1,10 +1,10 @@
 {
-    "predict_accuracy": 0.8892307692307693,
-    "predict_f1": 0.6833114323258869,
-    "predict_loss": 0.3853023946285248,
-    "predict_precision": 0.6718346253229974,
-    "predict_recall": 0.6951871657754011,
-    "predict_runtime": 1.5167,
-    "predict_samples_per_second": 11.868,
-    "predict_steps_per_second": 1.319
+    "predict_accuracy": 0.8218373936014088,
+    "predict_f1": 0.9038133181559477,
+    "predict_loss": 0.6888472437858582,
+    "predict_precision": 0.895152198421646,
+    "predict_recall": 0.9126436781609195,
+    "predict_runtime": 2.0596,
+    "predict_samples_per_second": 8.74,
+    "predict_steps_per_second": 0.971
 }

predictions.txt

@@ -1,18 +1,18 @@
-header header other question question question question header header header answer answer answer header question header question header question header question answer header question
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