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bert-uncased-massive-intent-classification-finetuned-banking
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: 2.5965
- Accuracy: 0.12
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.731 | 1.0 | 3 | 2.6423 | 0.1067 |
| 2.4424 | 2.0 | 6 | 2.6178 | 0.1067 |
| 2.2005 | 3.0 | 9 | 2.6028 | 0.1111 |
| 2.1954 | 4.0 | 12 | 2.5965 | 0.12 |
| 2.0599 | 5.0 | 15 | 2.5935 | 0.12 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.3.2
- Tokenizers 0.12.1
