End of training

README.md

@@ -12,29 +12,7 @@ metrics:
 - accuracy
 model-index:
 - name: ft-ms-layoutlmv3-funsd-layoutlmv3
-  results:
-  - task:
-      name: Token Classification
-      type: token-classification
-    dataset:
-      name: funsd-layoutlmv3
-      type: funsd-layoutlmv3
-      config: funsd
-      split: test
-      args: funsd
-    metrics:
-    - name: Precision
-      type: precision
-      value: 0.89171974522293
-    - name: Recall
-      type: recall
-      value: 0.9041231992051664
-    - name: F1
-      type: f1
-      value: 0.8978786383818451
-    - name: Accuracy
-      type: accuracy
-      value: 0.8377510994888863
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -42,13 +20,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # ft-ms-layoutlmv3-funsd-layoutlmv3
 
-This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the funsd-layoutlmv3 dataset.
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the aisuko/funsd-layoutlmv3 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.0021
-- Precision: 0.8917
-- Recall: 0.9041
-- F1: 0.8979
-- Accuracy: 0.8378
+- Loss: 0.6357
+- Precision: 0.8356
+- Recall: 0.8838
+- F1: 0.8590
+- Accuracy: 0.8029
 
 ## Model description
 
@@ -73,22 +51,15 @@ 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: 1000
+- training_steps: 200
+- mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 10.0  | 100  | 0.5222          | 0.8477    | 0.8823 | 0.8647 | 0.8436   |
-| No log        | 20.0  | 200  | 0.6686          | 0.8736    | 0.9026 | 0.8879 | 0.8357   |
-| No log        | 30.0  | 300  | 0.7175          | 0.8759    | 0.9151 | 0.8950 | 0.8286   |
-| No log        | 40.0  | 400  | 0.7636          | 0.8832    | 0.8977 | 0.8904 | 0.8426   |
-| 0.2392        | 50.0  | 500  | 0.9518          | 0.8820    | 0.9026 | 0.8922 | 0.8178   |
-| 0.2392        | 60.0  | 600  | 0.9803          | 0.8771    | 0.8897 | 0.8834 | 0.8121   |
-| 0.2392        | 70.0  | 700  | 1.0956          | 0.8883    | 0.9086 | 0.8983 | 0.8173   |
-| 0.2392        | 80.0  | 800  | 0.9517          | 0.8930    | 0.9076 | 0.9002 | 0.8444   |
-| 0.2392        | 90.0  | 900  | 1.0337          | 0.8950    | 0.9061 | 0.9005 | 0.8379   |
-| 0.0083        | 100.0 | 1000 | 1.0021          | 0.8917    | 0.9041 | 0.8979 | 0.8378   |
+| No log        | 10.0  | 100  | 0.5893          | 0.7972    | 0.8708 | 0.8324 | 0.8104   |
+| No log        | 20.0  | 200  | 0.6357          | 0.8356    | 0.8838 | 0.8590 | 0.8029   |
 
 
 ### Framework versions

model.safetensors

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 size 501355532

training_args.bin

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+oid sha256:fb87cfa40858053cb17d836ca35b98b6f88ff9dec42a54f8cac9833c7f07533e
 size 4155