Model save

README.md

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+---
+license: cc-by-nc-sa-4.0
+base_model: microsoft/layoutlmv3-base
+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: 0.4174757281553398
+    - name: Recall
+      type: recall
+      value: 0.4505988023952096
+    - name: F1
+      type: f1
+      value: 0.43340532757379413
+    - name: Accuracy
+      type: accuracy
+      value: 0.35059422750424446
+---
+
+<!-- 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: 3.4767
+- Precision: 0.4175
+- Recall: 0.4506
+- F1: 0.4334
+- Accuracy: 0.3506
+
+## 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: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.5   | 20   | 3.5573          | 0.3937    | 0.4558 | 0.4225 | 0.3587   |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.1.1+cpu
+- Datasets 2.20.0
+- Tokenizers 0.19.1

runs/Jul15_15-56-08_DESKTOP-L6742S8/events.out.tfevents.1721039824.DESKTOP-L6742S8.9224.1

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