update model card README.md

README.md

@@ -0,0 +1,71 @@
+---
+license: cc-by-nc-sa-4.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: EElayoutlmv3_jordyvl_rvl_cdip_easyocr_2023-05-22_loss_subgraphs
+  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. -->
+
+# EElayoutlmv3_jordyvl_rvl_cdip_easyocr_2023-05-22_loss_subgraphs
+
+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: 0.2391
+- Accuracy: 0.9343
+- Exit 0 Accuracy: 0.3283
+- Exit 1 Accuracy: 0.4678
+- Exit 2 Accuracy: 0.8356
+- Exit 3 Accuracy: 0.9082
+- Exit 4 Accuracy: 0.9331
+
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 32
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Exit 0 Accuracy | Exit 1 Accuracy | Exit 2 Accuracy | Exit 3 Accuracy | Exit 4 Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:---------------:|:---------------:|:---------------:|:---------------:|
+| 0.4036        | 1.0   | 1250 | 0.3090          | 0.9140   | 0.2036          | 0.3108          | 0.7504          | 0.8722          | 0.9108          |
+| 0.2783        | 2.0   | 2500 | 0.2730          | 0.9221   | 0.2715          | 0.3928          | 0.7959          | 0.8902          | 0.9227          |
+| 0.2376        | 3.0   | 3750 | 0.2487          | 0.9284   | 0.2865          | 0.4313          | 0.8182          | 0.9000          | 0.9280          |
+| 0.1984        | 4.0   | 5000 | 0.2446          | 0.9314   | 0.3150          | 0.4529          | 0.8282          | 0.9033          | 0.9301          |
+| 0.1729        | 5.0   | 6250 | 0.2424          | 0.9327   | 0.3240          | 0.4636          | 0.8331          | 0.9076          | 0.9323          |
+| 0.1524        | 6.0   | 7500 | 0.2391          | 0.9343   | 0.3283          | 0.4678          | 0.8356          | 0.9082          | 0.9331          |
+
+
+### Framework versions
+
+- Transformers 4.26.1
+- Pytorch 1.13.1.post200
+- Datasets 2.9.0
+- Tokenizers 0.13.2