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: LayoutLM_1
+  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. -->
+
+# LayoutLM_1
+
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4204
+- Precision: 0.6552
+- Recall: 0.7480
+- F1: 0.6985
+- Accuracy: 0.9071
+
+## 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        | 3.7   | 100  | 0.6185          | 0.0       | 0.0    | 0.0    | 0.8310   |
+| No log        | 7.41  | 200  | 0.4585          | 0.6146    | 0.4646 | 0.5291 | 0.8839   |
+| No log        | 11.11 | 300  | 0.4020          | 0.5870    | 0.6378 | 0.6113 | 0.8929   |
+| No log        | 14.81 | 400  | 0.3775          | 0.6496    | 0.7008 | 0.6742 | 0.9006   |
+| 0.4776        | 18.52 | 500  | 0.3826          | 0.6268    | 0.7008 | 0.6617 | 0.9019   |
+| 0.4776        | 22.22 | 600  | 0.3864          | 0.6224    | 0.7008 | 0.6593 | 0.8981   |
+| 0.4776        | 25.93 | 700  | 0.4307          | 0.5759    | 0.7165 | 0.6386 | 0.8916   |
+| 0.4776        | 29.63 | 800  | 0.4205          | 0.6738    | 0.7480 | 0.7090 | 0.9123   |
+| 0.4776        | 33.33 | 900  | 0.4176          | 0.6552    | 0.7480 | 0.6985 | 0.9084   |
+| 0.0536        | 37.04 | 1000 | 0.4204          | 0.6552    | 0.7480 | 0.6985 | 0.9071   |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3

runs/Aug26_17-38-29_a211cf088ab3/events.out.tfevents.1693071521.a211cf088ab3.4821.0

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