update model card README.md

README.md

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+---
+license: cc-by-nc-sa-4.0
+tags:
+- generated_from_trainer
+datasets:
+- cord-layoutlmv3
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: project-ocr
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: cord-layoutlmv3
+      type: cord-layoutlmv3
+      config: cord
+      split: test
+      args: cord
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.7515745276417075
+    - name: Recall
+      type: recall
+      value: 0.8038922155688623
+    - name: F1
+      type: f1
+      value: 0.7768535262206148
+    - name: Accuracy
+      type: accuracy
+      value: 0.8102716468590832
+---
+
+<!-- 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. -->
+
+# project-ocr
+
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the cord-layoutlmv3 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9877
+- Precision: 0.7516
+- Recall: 0.8039
+- F1: 0.7769
+- Accuracy: 0.8103
+
+## 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: 5
+- eval_batch_size: 5
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 500
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.83  | 50   | 2.6184          | 0.4355    | 0.5404 | 0.4823 | 0.4338   |
+| No log        | 1.67  | 100  | 1.8766          | 0.5912    | 0.6018 | 0.5964 | 0.5620   |
+| No log        | 2.5   | 150  | 1.6165          | 0.5737    | 0.6347 | 0.6027 | 0.6150   |
+| No log        | 3.33  | 200  | 1.4317          | 0.5732    | 0.6737 | 0.6194 | 0.6944   |
+| No log        | 4.17  | 250  | 1.2787          | 0.6190    | 0.7126 | 0.6625 | 0.7347   |
+| No log        | 5.0   | 300  | 1.1632          | 0.6729    | 0.7560 | 0.7120 | 0.7759   |
+| No log        | 5.83  | 350  | 1.0990          | 0.6980    | 0.7665 | 0.7306 | 0.7857   |
+| No log        | 6.67  | 400  | 1.0327          | 0.7125    | 0.7792 | 0.7444 | 0.7946   |
+| No log        | 7.5   | 450  | 0.9994          | 0.7526    | 0.8016 | 0.7764 | 0.8065   |
+| 1.6589        | 8.33  | 500  | 0.9877          | 0.7516    | 0.8039 | 0.7769 | 0.8103   |
+
+
+### Framework versions
+
+- Transformers 4.27.1
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.1
+- Tokenizers 0.13.2