update model card README.md

README.md

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+---
+license: cc-by-nc-sa-4.0
+tags:
+- generated_from_trainer
+datasets:
+- data_registros_layoutv3
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: layoutlmv3-finetuned-registros_v2
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: data_registros_layoutv3
+      type: data_registros_layoutv3
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.860632183908046
+    - name: Recall
+      type: recall
+      value: 0.9374021909233177
+    - name: F1
+      type: f1
+      value: 0.8973782771535581
+    - name: Accuracy
+      type: accuracy
+      value: 0.9816688664026983
+---
+
+<!-- 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-registros_v2
+
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the data_registros_layoutv3 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1473
+- Precision: 0.8606
+- Recall: 0.9374
+- F1: 0.8974
+- Accuracy: 0.9817
+
+## 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: 5e-06
+- train_batch_size: 4
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 10.87 | 250  | 0.4204          | 0.4257    | 0.4351 | 0.4303 | 0.9104   |
+| 0.6077        | 21.74 | 500  | 0.2246          | 0.7957    | 0.8654 | 0.8291 | 0.9683   |
+| 0.6077        | 32.61 | 750  | 0.1636          | 0.8438    | 0.9218 | 0.8811 | 0.9765   |
+| 0.1638        | 43.48 | 1000 | 0.1473          | 0.8606    | 0.9374 | 0.8974 | 0.9817   |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3