ad-classifier
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0942
- Accuracy: 0.9799
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 112 | 0.1198 | 0.9749 |
| No log | 2.0 | 224 | 0.0874 | 0.9698 |
| No log | 3.0 | 336 | 0.1638 | 0.9598 |
| No log | 4.0 | 448 | 0.1002 | 0.9799 |
| 0.1595 | 5.0 | 560 | 0.0942 | 0.9799 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.0
- Tokenizers 0.13.3
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Model tree for Joshnicholas/ad-classifier
Base model
distilbert/distilbert-base-uncased