Upload TFLayoutLMForTokenClassification

README.md

@@ -3,24 +3,24 @@ base_model: microsoft/layoutlm-base-uncased
 tags:
 - generated_from_keras_callback
 model-index:
-- name: stevethecur/layoutlm-funsd-tf
+- name: layoutlm-funsd-tf
   results: []
 ---
 
 <!-- This model card has been generated automatically according to the information Keras had access to. You should
 probably proofread and complete it, then remove this comment. -->
 
-# stevethecur/layoutlm-funsd-tf
+# layoutlm-funsd-tf
 
 This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Train Loss: 0.2843
-- Validation Loss: 0.6247
-- Train Overall Precision: 0.7359
-- Train Overall Recall: 0.8038
-- Train Overall F1: 0.7683
-- Train Overall Accuracy: 0.8182
-- Epoch: 6
+- Train Loss: 0.2389
+- Validation Loss: 0.6400
+- Train Overall Precision: 0.7230
+- Train Overall Recall: 0.8043
+- Train Overall F1: 0.7615
+- Train Overall Accuracy: 0.8148
+- Epoch: 7
 
 ## Model description
 
@@ -53,6 +53,7 @@ The following hyperparameters were used during training:
 | 0.4399     | 0.6261          | 0.7078                  | 0.7863               | 0.7449           | 0.8077                 | 4     |
 | 0.3561     | 0.6431          | 0.7204                  | 0.7757               | 0.7470           | 0.8067                 | 5     |
 | 0.2843     | 0.6247          | 0.7359                  | 0.8038               | 0.7683           | 0.8182                 | 6     |
+| 0.2389     | 0.6400          | 0.7230                  | 0.8043               | 0.7615           | 0.8148                 | 7     |
 
 
 ### Framework versions

tf_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7d7acd60aee464b12c022955866319ce8bf1769bea83bd153c222f742f6fcaf1
+oid sha256:f6cf8507f0eb0b62576ca25e67bbb27a53011fba275bc635e067b84ad127e346
 size 450829256