Layoutlmv3-finetuned-DocLayNet-test
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: 0.5038
- Precision: 0.5207
- Recall: 0.7112
- F1: 0.6012
- Accuracy: 0.8421
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
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1000
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
1.5092 | 0.37 | 250 | 0.8072 | 0.1922 | 0.2342 | 0.2111 | 0.8227 |
0.8608 | 0.73 | 500 | 0.6402 | 0.3963 | 0.6108 | 0.4807 | 0.8596 |
0.6463 | 1.1 | 750 | 0.8042 | 0.5702 | 0.6297 | 0.5985 | 0.8080 |
0.4495 | 1.46 | 1000 | 0.8439 | 0.5353 | 0.6234 | 0.5760 | 0.8033 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Downloads last month
- 9
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for mckabue/Layoutlmv3-finetuned-DocLayNet-test
Base model
microsoft/layoutlmv3-baseEvaluation results
- Precision on doc_lay_net-smalltest set self-reported0.521
- Recall on doc_lay_net-smalltest set self-reported0.711
- F1 on doc_lay_net-smalltest set self-reported0.601
- Accuracy on doc_lay_net-smalltest set self-reported0.842