update model card README.md

README.md

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+---
+license: cc-by-nc-sa-4.0
+tags:
+- generated_from_trainer
+datasets:
+- doc_lay_net-small
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: layoutlmv3-finetuned-DocLayNet
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: doc_lay_net-small
+      type: doc_lay_net-small
+      config: DocLayNet_2022.08_processed_on_2023.01
+      split: test
+      args: DocLayNet_2022.08_processed_on_2023.01
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.6178861788617886
+    - name: Recall
+      type: recall
+      value: 0.7238095238095238
+    - name: F1
+      type: f1
+      value: 0.6666666666666667
+    - name: Accuracy
+      type: accuracy
+      value: 0.8719611021069692
+---
+
+<!-- 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-DocLayNet
+
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the doc_lay_net-small dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5644
+- Precision: 0.6179
+- Recall: 0.7238
+- F1: 0.6667
+- Accuracy: 0.8720
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 2
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 1000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 1.3383        | 0.58  | 200  | 0.8358          | 0.3007    | 0.4381 | 0.3566 | 0.7724   |
+| 0.8308        | 1.16  | 400  | 0.6735          | 0.4634    | 0.5429 | 0.5    | 0.8084   |
+| 0.518         | 1.74  | 600  | 0.5706          | 0.5373    | 0.6857 | 0.6025 | 0.8399   |
+| 0.3856        | 2.33  | 800  | 0.6303          | 0.6032    | 0.7238 | 0.6580 | 0.8648   |
+| 0.2558        | 2.91  | 1000 | 0.5644          | 0.6179    | 0.7238 | 0.6667 | 0.8720   |
+
+
+### Framework versions
+
+- Transformers 4.27.3
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.1
+- Tokenizers 0.13.2