update model card README.md

README.md

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+---
+license: cc-by-nc-sa-4.0
+tags:
+- generated_from_trainer
+datasets:
+- invoice_layoutlmv3
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: layoutlmv3-finetuned-intellectai
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: invoice_layoutlmv3
+      type: invoice_layoutlmv3
+      config: intellectai
+      split: validation
+      args: intellectai
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.7053571428571429
+    - name: Recall
+      type: recall
+      value: 0.8540540540540541
+    - name: F1
+      type: f1
+      value: 0.7726161369193154
+    - name: Accuracy
+      type: accuracy
+      value: 0.9624772313296903
+---
+
+<!-- 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-intellectai
+
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the invoice_layoutlmv3 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3645
+- Precision: 0.7054
+- Recall: 0.8541
+- F1: 0.7726
+- Accuracy: 0.9625
+
+## 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: 2
+- 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        | 0.79  | 50   | 1.7979          | 0.0228    | 0.0541 | 0.0321 | 0.1410   |
+| No log        | 1.59  | 100  | 1.2400          | 0.0863    | 0.4216 | 0.1433 | 0.2616   |
+| No log        | 2.38  | 150  | 0.8691          | 0.1279    | 0.6919 | 0.2159 | 0.4495   |
+| No log        | 3.17  | 200  | 0.6001          | 0.2323    | 0.8162 | 0.3617 | 0.7570   |
+| No log        | 3.97  | 250  | 0.4709          | 0.4660    | 0.7784 | 0.5830 | 0.9093   |
+| No log        | 4.76  | 300  | 0.3986          | 0.5977    | 0.8270 | 0.6939 | 0.9472   |
+| No log        | 5.56  | 350  | 0.3762          | 0.5714    | 0.8216 | 0.6741 | 0.9454   |
+| No log        | 6.35  | 400  | 0.3763          | 0.7048    | 0.8649 | 0.7767 | 0.9636   |
+| No log        | 7.14  | 450  | 0.3696          | 0.6639    | 0.8541 | 0.7470 | 0.9570   |
+| 0.71          | 7.94  | 500  | 0.3645          | 0.7054    | 0.8541 | 0.7726 | 0.9625   |
+
+
+### Framework versions
+
+- Transformers 4.27.1
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.1
+- Tokenizers 0.13.2