Instructions to use Deehan1866/deberta-wic-angle3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Deehan1866/deberta-wic-angle3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Deehan1866/deberta-wic-angle3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Deehan1866/deberta-wic-angle3") model = AutoModelForSequenceClassification.from_pretrained("Deehan1866/deberta-wic-angle3") - Notebooks
- Google Colab
- Kaggle
deberta-wic-angle3
This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1912
- Accuracy: 0.9687
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use 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_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2234 | 1.0 | 170 | 0.1966 | 0.9530 |
| 0.1351 | 2.0 | 340 | 0.1612 | 0.9624 |
| 0.1019 | 3.0 | 510 | 0.1375 | 0.9624 |
| 0.0831 | 4.0 | 680 | 0.1117 | 0.9687 |
| 0.0448 | 5.0 | 850 | 0.1555 | 0.9655 |
| 0.0217 | 6.0 | 1020 | 0.1744 | 0.9687 |
| 0.0262 | 7.0 | 1190 | 0.1912 | 0.9687 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.8.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2
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Model tree for Deehan1866/deberta-wic-angle3
Base model
microsoft/deberta-v3-large