layoutlmv3-finetuned-cord_100

README.md

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+---
+license: cc-by-nc-sa-4.0
+base_model: microsoft/layoutlmv3-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: layoutlmv3-finetuned-cord_100
+  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-finetuned-cord_100
+
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2879
+- Precision: 0.9258
+- Recall: 0.9384
+- F1: 0.9321
+- Accuracy: 0.9474
+
+## 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: 2500
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 4.17  | 250  | 0.6982          | 0.7974    | 0.8017 | 0.7995 | 0.8265   |
+| 0.9999        | 8.33  | 500  | 0.4214          | 0.8603    | 0.8754 | 0.8678 | 0.8936   |
+| 0.9999        | 12.5  | 750  | 0.2820          | 0.9081    | 0.9164 | 0.9123 | 0.9364   |
+| 0.1912        | 16.67 | 1000 | 0.2710          | 0.9147    | 0.9293 | 0.9220 | 0.9389   |
+| 0.1912        | 20.83 | 1250 | 0.2748          | 0.9125    | 0.9271 | 0.9197 | 0.9406   |
+| 0.061         | 25.0  | 1500 | 0.2612          | 0.9220    | 0.9339 | 0.9279 | 0.9474   |
+| 0.061         | 29.17 | 1750 | 0.2731          | 0.9300    | 0.9384 | 0.9342 | 0.9478   |
+| 0.0275        | 33.33 | 2000 | 0.2824          | 0.9279    | 0.9384 | 0.9331 | 0.9487   |
+| 0.0275        | 37.5  | 2250 | 0.2886          | 0.9242    | 0.9362 | 0.9302 | 0.9457   |
+| 0.0168        | 41.67 | 2500 | 0.2879          | 0.9258    | 0.9384 | 0.9321 | 0.9474   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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runs/Jan23_11-37-11_22210d714ca2/events.out.tfevents.1706009832.22210d714ca2.169.0

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