delivery-range-distilbert-base-uncased
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8847
- Accuracy: 0.7895
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: 70
- eval_batch_size: 70
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 4 | 0.6916 | 0.4737 |
No log | 2.0 | 8 | 0.6498 | 0.6711 |
No log | 3.0 | 12 | 0.6176 | 0.6711 |
No log | 4.0 | 16 | 0.5565 | 0.75 |
No log | 5.0 | 20 | 0.5144 | 0.7763 |
No log | 6.0 | 24 | 0.5000 | 0.75 |
No log | 7.0 | 28 | 0.4871 | 0.7763 |
No log | 8.0 | 32 | 0.5156 | 0.7632 |
No log | 9.0 | 36 | 0.4752 | 0.7632 |
No log | 10.0 | 40 | 0.5275 | 0.7763 |
No log | 11.0 | 44 | 0.5372 | 0.7632 |
No log | 12.0 | 48 | 0.5400 | 0.75 |
No log | 13.0 | 52 | 0.5988 | 0.7632 |
No log | 14.0 | 56 | 0.5852 | 0.7763 |
No log | 15.0 | 60 | 0.6477 | 0.8026 |
No log | 16.0 | 64 | 0.6769 | 0.7895 |
No log | 17.0 | 68 | 0.7157 | 0.7895 |
No log | 18.0 | 72 | 0.7398 | 0.7763 |
No log | 19.0 | 76 | 0.7651 | 0.7763 |
No log | 20.0 | 80 | 0.7922 | 0.7895 |
No log | 21.0 | 84 | 0.8137 | 0.7895 |
No log | 22.0 | 88 | 0.8256 | 0.7895 |
No log | 23.0 | 92 | 0.8343 | 0.7763 |
No log | 24.0 | 96 | 0.8493 | 0.7763 |
No log | 25.0 | 100 | 0.8650 | 0.7895 |
No log | 26.0 | 104 | 0.8728 | 0.7895 |
No log | 27.0 | 108 | 0.8789 | 0.7895 |
No log | 28.0 | 112 | 0.8826 | 0.7895 |
No log | 29.0 | 116 | 0.8841 | 0.7895 |
No log | 30.0 | 120 | 0.8847 | 0.7895 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.0
- Datasets 2.20.0
- Tokenizers 0.19.1
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