DistilBERT-finetuned-customer-queries
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1443
- Accuracy: 0.9935
- F1: 0.9935
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.6111 | 1.0 | 250 | 0.3456 | 0.9895 | 0.9895 |
| 0.264 | 2.0 | 500 | 0.1443 | 0.9935 | 0.9935 |
Framework versions
- Transformers 4.42.1
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for SebaK13/DistilBERT-finetuned-customer-queries
Base model
distilbert/distilbert-base-uncased