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: layoutlmv3-finetuned-cord_100
+  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: 0.4115296803652968
+    - name: Recall
+      type: recall
+      value: 0.5396706586826348
+    - name: F1
+      type: f1
+      value: 0.46696891191709844
+    - name: Accuracy
+      type: accuracy
+      value: 0.4350594227504245
+---
+
+<!-- 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_100
+
+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: 2.5624
+- Precision: 0.4115
+- Recall: 0.5397
+- F1: 0.4670
+- Accuracy: 0.4351
+
+## 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: 100
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.06  | 10   | 3.8065          | 0.1637    | 0.2582 | 0.2003 | 0.2585   |
+| No log        | 0.12  | 20   | 3.4787          | 0.4661    | 0.3862 | 0.4224 | 0.3353   |
+| No log        | 0.19  | 30   | 3.2587          | 0.4332    | 0.4731 | 0.4522 | 0.3667   |
+| No log        | 0.25  | 40   | 3.0615          | 0.4144    | 0.4873 | 0.4479 | 0.3846   |
+| No log        | 0.31  | 50   | 2.9052          | 0.3993    | 0.5090 | 0.4475 | 0.4024   |
+| No log        | 0.38  | 60   | 2.7819          | 0.3876    | 0.5165 | 0.4429 | 0.4143   |
+| No log        | 0.44  | 70   | 2.6853          | 0.3891    | 0.5202 | 0.4452 | 0.4164   |
+| No log        | 0.5   | 80   | 2.6245          | 0.3942    | 0.5269 | 0.4510 | 0.4236   |
+| No log        | 0.56  | 90   | 2.5777          | 0.4056    | 0.5352 | 0.4614 | 0.4312   |
+| No log        | 0.62  | 100  | 2.5624          | 0.4115    | 0.5397 | 0.4670 | 0.4351   |
+
+
+### Framework versions
+
+- Transformers 4.28.0
+- Pytorch 2.0.1+cpu
+- Datasets 2.12.0
+- Tokenizers 0.13.3