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bert-uncased-massive-intent-classification-banking-1
This model is a fine-tuned version of gokuls/bert-uncased-massive-intent-classification on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.7010
- Accuracy: 0.1289
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: 2e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.6675 | 1.0 | 3 | 2.7010 | 0.1289 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.3.2
- Tokenizers 0.12.1
