Instructions to use Xyren2005/masker_roberta_tab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Xyren2005/masker_roberta_tab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Xyren2005/masker_roberta_tab")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Xyren2005/masker_roberta_tab") model = AutoModelForTokenClassification.from_pretrained("Xyren2005/masker_roberta_tab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
masker_roberta_tab
This model is a fine-tuned version of Xyren2005/pii-ner-roberta on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2644
- F1: 0.7771
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: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 690
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 1.4569 | 1.0 | 432 | 0.3458 | 0.6424 |
| 0.9550 | 2.0 | 864 | 0.2821 | 0.7113 |
| 0.8613 | 3.0 | 1296 | 0.2537 | 0.7516 |
| 0.6801 | 4.0 | 1728 | 0.2621 | 0.7627 |
| 0.6021 | 5.0 | 2160 | 0.2660 | 0.7717 |
| 0.6453 | 6.0 | 2592 | 0.2556 | 0.7755 |
| 0.5729 | 7.0 | 3024 | 0.2643 | 0.7771 |
| 0.5301 | 8.0 | 3456 | 0.2690 | 0.7752 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
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Model tree for Xyren2005/masker_roberta_tab
Base model
Xyren2005/pii-ner-roberta