End of training

README.md

@@ -1,30 +1,50 @@
 ---
-license: cc-by-nc-sa-4.0
-base_model: microsoft/layoutlmv3-base
+base_model: layoutlmv3
 tags:
 - generated_from_trainer
+datasets:
+- mp-02/cord
 metrics:
 - precision
 - recall
 - f1
 - accuracy
 model-index:
-- name: layoutlmv3-finetuned-cord_200
-  results: []
+- name: layoutlmv3-finetuned-cord
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: mp-02/cord
+      type: mp-02/cord
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.963984674329502
+    - name: Recall
+      type: recall
+      value: 0.9767080745341615
+    - name: F1
+      type: f1
+      value: 0.9703046664095644
+    - name: Accuracy
+      type: accuracy
+      value: 0.9690152801358234
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# layoutlmv3-finetuned-cord_200
+# layoutlmv3-finetuned-cord
 
-This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
+This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the mp-02/cord dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2000
-- Precision: 0.9557
-- Recall: 0.9713
-- F1: 0.9634
-- Accuracy: 0.9648
+- Loss: 0.2087
+- Precision: 0.9640
+- Recall: 0.9767
+- F1: 0.9703
+- Accuracy: 0.9690
 
 ## Model description
 
@@ -49,14 +69,20 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- training_steps: 200
+- training_steps: 2000
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 0.625 | 100  | 0.2075          | 0.9483    | 0.9689 | 0.9585 | 0.9618   |
-| No log        | 1.25  | 200  | 0.2000          | 0.9557    | 0.9713 | 0.9634 | 0.9648   |
+| Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.5625  | 250  | 0.2302          | 0.9594    | 0.9720 | 0.9657 | 0.9656   |
+| 0.041         | 3.125   | 500  | 0.2176          | 0.9542    | 0.9705 | 0.9623 | 0.9618   |
+| 0.041         | 4.6875  | 750  | 0.1903          | 0.9573    | 0.9736 | 0.9654 | 0.9682   |
+| 0.0302        | 6.25    | 1000 | 0.2027          | 0.9602    | 0.9744 | 0.9672 | 0.9660   |
+| 0.0302        | 7.8125  | 1250 | 0.2174          | 0.9670    | 0.9775 | 0.9722 | 0.9703   |
+| 0.019         | 9.375   | 1500 | 0.2018          | 0.9640    | 0.9775 | 0.9707 | 0.9711   |
+| 0.019         | 10.9375 | 1750 | 0.2084          | 0.9677    | 0.9783 | 0.9730 | 0.9694   |
+| 0.0115        | 12.5    | 2000 | 0.2087          | 0.9640    | 0.9767 | 0.9703 | 0.9690   |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:66e6f6604832b619df85b7dfb01b48c638376529052830a583f60dabe2b74313
+oid sha256:409d5ca371e1d810ffa19a50eb8ef027e3d107d4f9e1515e9720afae50f354e3
 size 503816564