deberta-v3-bass-complex-questions_classifier
This model is a fine-tuned version of sileod/deberta-v3-base-tasksource-nli on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0001
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
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: 8
- eval_batch_size: 8
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0532 | 2.3585 | 500 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.19.1
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Model tree for nogae/deberta-v3-bass-complex-questions_classifier
Base model
sileod/deberta-v3-base-tasksource-nli