End of training

README.md

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+---
+library_name: transformers
+license: cc-by-nc-sa-4.0
+base_model: microsoft/layoutlmv3-base
+tags:
+- generated_from_trainer
+datasets:
+- doc_lay_net-small
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: LayoutLMv3-DocLayNet-small
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: doc_lay_net-small
+      type: doc_lay_net-small
+      config: DocLayNet_2022.08_processed_on_2023.01
+      split: validation
+      args: DocLayNet_2022.08_processed_on_2023.01
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.12834224598930483
+    - name: Recall
+      type: recall
+      value: 0.0759493670886076
+    - name: F1
+      type: f1
+      value: 0.09542743538767395
+    - name: Accuracy
+      type: accuracy
+      value: 0.6476804585348379
+---
+
+<!-- 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-DocLayNet-small
+
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the doc_lay_net-small dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2781
+- Precision: 0.1283
+- Recall: 0.0759
+- F1: 0.0954
+- Accuracy: 0.6477
+
+## 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: 3e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 256
+- total_eval_batch_size: 16
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.4.1
+- Datasets 3.5.1
+- Tokenizers 0.21.1