End of training

README.md

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+---
+license: cc-by-nc-sa-4.0
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: LayoutLMv3_large_2
+  results: []
+---
+
+<!-- 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_large_2
+
+This model is a fine-tuned version of [BadreddineHug/LayoutLM_5](https://huggingface.co/BadreddineHug/LayoutLM_5) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4678
+- Precision: 0.7444
+- Recall: 0.8462
+- F1: 0.792
+- Accuracy: 0.9431
+
+## 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
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 2000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 2.44  | 100  | 0.2604          | 0.8049    | 0.8462 | 0.8250 | 0.9487   |
+| No log        | 4.88  | 200  | 0.2887          | 0.6923    | 0.8462 | 0.7615 | 0.9294   |
+| No log        | 7.32  | 300  | 0.3961          | 0.6711    | 0.8547 | 0.7519 | 0.9248   |
+| No log        | 9.76  | 400  | 0.3117          | 0.7778    | 0.8376 | 0.8066 | 0.9465   |
+| 0.1255        | 12.2  | 500  | 0.3344          | 0.7698    | 0.8291 | 0.7984 | 0.9419   |
+| 0.1255        | 14.63 | 600  | 0.3892          | 0.7197    | 0.8120 | 0.7631 | 0.9339   |
+| 0.1255        | 17.07 | 700  | 0.3865          | 0.7143    | 0.8547 | 0.7782 | 0.9419   |
+| 0.1255        | 19.51 | 800  | 0.4737          | 0.6690    | 0.8291 | 0.7405 | 0.9226   |
+| 0.1255        | 21.95 | 900  | 0.3876          | 0.7405    | 0.8291 | 0.7823 | 0.9442   |
+| 0.0206        | 24.39 | 1000 | 0.3845          | 0.7444    | 0.8462 | 0.792  | 0.9465   |
+| 0.0206        | 26.83 | 1100 | 0.4179          | 0.75      | 0.8205 | 0.7837 | 0.9442   |
+| 0.0206        | 29.27 | 1200 | 0.3942          | 0.7576    | 0.8547 | 0.8032 | 0.9510   |
+| 0.0206        | 31.71 | 1300 | 0.4521          | 0.7293    | 0.8291 | 0.776  | 0.9408   |
+| 0.0206        | 34.15 | 1400 | 0.4725          | 0.7050    | 0.8376 | 0.7656 | 0.9328   |
+| 0.0051        | 36.59 | 1500 | 0.4874          | 0.6849    | 0.8547 | 0.7605 | 0.9317   |
+| 0.0051        | 39.02 | 1600 | 0.4366          | 0.7519    | 0.8547 | 0.8    | 0.9453   |
+| 0.0051        | 41.46 | 1700 | 0.4978          | 0.6897    | 0.8547 | 0.7634 | 0.9317   |
+| 0.0051        | 43.9  | 1800 | 0.4599          | 0.7444    | 0.8462 | 0.792  | 0.9431   |
+| 0.0051        | 46.34 | 1900 | 0.4765          | 0.7372    | 0.8632 | 0.7953 | 0.9431   |
+| 0.002         | 48.78 | 2000 | 0.4678          | 0.7444    | 0.8462 | 0.792  | 0.9431   |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3

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