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: model-v2-2024-05-07
+  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. -->
+
+# model-v2-2024-05-07
+
+This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8052
+- Precision: 0.6764
+- Recall: 0.6050
+- F1: 0.6387
+- Accuracy: 0.8195
+
+## 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: 1000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.9   | 100  | 1.3581          | 0.3509    | 0.0474 | 0.0836 | 0.6756   |
+| No log        | 1.8   | 200  | 1.0434          | 0.5730    | 0.4235 | 0.4870 | 0.7685   |
+| No log        | 2.7   | 300  | 0.8190          | 0.6662    | 0.5777 | 0.6188 | 0.8112   |
+| No log        | 3.6   | 400  | 0.7884          | 0.6662    | 0.5753 | 0.6174 | 0.8108   |
+| 0.962         | 4.5   | 500  | 0.7199          | 0.6835    | 0.6251 | 0.6530 | 0.8250   |
+| 0.962         | 5.41  | 600  | 0.7505          | 0.6807    | 0.6145 | 0.6459 | 0.8235   |
+| 0.962         | 6.31  | 700  | 0.7669          | 0.6641    | 0.6168 | 0.6396 | 0.8188   |
+| 0.962         | 7.21  | 800  | 0.7707          | 0.6747    | 0.6002 | 0.6353 | 0.8188   |
+| 0.962         | 8.11  | 900  | 0.7751          | 0.6765    | 0.6251 | 0.6498 | 0.8235   |
+| 0.3828        | 9.01  | 1000 | 0.8052          | 0.6764    | 0.6050 | 0.6387 | 0.8195   |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.13.3

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