layoutlmv2-finetuned-piimask
This model is a fine-tuned version of microsoft/layoutlmv2-large-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1939
- Precision: 0.7555
- Recall: 0.7775
- F1: 0.7663
- Accuracy: 0.9581
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 135 | 0.1473 | 0.7251 | 0.6697 | 0.6963 | 0.9499 |
No log | 2.0 | 270 | 0.1400 | 0.6767 | 0.7573 | 0.7147 | 0.9621 |
No log | 3.0 | 405 | 0.1543 | 0.7372 | 0.7753 | 0.7558 | 0.9612 |
0.3116 | 4.0 | 540 | 0.2355 | 0.7621 | 0.7775 | 0.7697 | 0.9560 |
0.3116 | 5.0 | 675 | 0.1939 | 0.7555 | 0.7775 | 0.7663 | 0.9581 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Downloads last month
- 78
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Model tree for vaibhav1411/layoutlmv2-finetuned-piimask
Base model
microsoft/layoutlmv2-large-uncased