intent_classification_model_fix
This model is a fine-tuned version of qanastek/XLMRoberta-Alexa-Intents-Classification on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1868
- Accuracy: 0.9773
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: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 4.0 | 208 | 1.1635 | 0.7728 |
| No log | 8.0 | 416 | 0.4652 | 0.9158 |
| 1.1894 | 12.0 | 624 | 0.2790 | 0.9546 |
| 1.1894 | 16.0 | 832 | 0.2050 | 0.9735 |
| 0.4709 | 20.0 | 1040 | 0.1868 | 0.9773 |
Framework versions
- Transformers 4.41.2
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
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