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bert-uncased-massive-intent-classification-finetuned-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: 2.6447
- Accuracy: 0.1822
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 |
|---|---|---|---|---|
| 2.9685 | 1.0 | 3 | 2.7310 | 0.1422 |
| 2.8056 | 2.0 | 6 | 2.6970 | 0.1467 |
| 2.5004 | 3.0 | 9 | 2.6680 | 0.1511 |
| 2.445 | 4.0 | 12 | 2.6515 | 0.1778 |
| 2.3977 | 5.0 | 15 | 2.6447 | 0.1822 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.3.2
- Tokenizers 0.12.1
