intent_classification_model
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: 0.3184
- Accuracy: 0.9409
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: 128
- eval_batch_size: 128
- 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 |
|---|---|---|---|---|
| 1.1893 | 4.0 | 712 | 1.0851 | 0.6870 |
| 0.6443 | 8.0 | 1424 | 0.6027 | 0.8489 |
| 0.294 | 12.0 | 2136 | 0.3864 | 0.9179 |
| 0.2081 | 16.0 | 2848 | 0.3309 | 0.9369 |
| 0.1274 | 20.0 | 3560 | 0.3184 | 0.9409 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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