layoutlmv3-finetuned-DocLayNet
This model is a fine-tuned version of microsoft/layoutlmv3-base on the doc_lay_net-small dataset. It achieves the following results on the evaluation set:
- Loss: 0.4878
- Precision: 0.8762
- Recall: 0.8762
- F1: 0.8762
- Accuracy: 0.8762
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
1.1244 | 2.9070 | 250 | 0.7630 | 0.7337 | 0.7337 | 0.7337 | 0.7337 |
0.2934 | 5.8140 | 500 | 0.4878 | 0.8762 | 0.8762 | 0.8762 | 0.8762 |
0.1028 | 8.7209 | 750 | 0.5626 | 0.8752 | 0.8752 | 0.8752 | 0.8752 |
0.0539 | 11.6279 | 1000 | 0.6090 | 0.8719 | 0.8719 | 0.8719 | 0.8719 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Model tree for Abinaya/layoutlmv3-finetuned-DocLayNet
Base model
microsoft/layoutlmv3-baseEvaluation results
- Precision on doc_lay_net-smalltest set self-reported0.876
- Recall on doc_lay_net-smalltest set self-reported0.876
- F1 on doc_lay_net-smalltest set self-reported0.876
- Accuracy on doc_lay_net-smalltest set self-reported0.876