brand-safety-classifier
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3403
- Accuracy: 0.5726
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: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 119 | 2.9720 | 0.2989 |
No log | 2.0 | 238 | 2.2252 | 0.5179 |
No log | 3.0 | 357 | 1.7828 | 0.5663 |
No log | 4.0 | 476 | 1.5521 | 0.5789 |
2.2394 | 5.0 | 595 | 1.4689 | 0.5832 |
2.2394 | 6.0 | 714 | 1.4107 | 0.5958 |
2.2394 | 7.0 | 833 | 1.4512 | 0.5937 |
2.2394 | 8.0 | 952 | 1.4819 | 0.5747 |
0.7869 | 9.0 | 1071 | 1.4911 | 0.5832 |
0.7869 | 10.0 | 1190 | 1.5625 | 0.5768 |
0.7869 | 11.0 | 1309 | 1.5715 | 0.5768 |
0.7869 | 12.0 | 1428 | 1.6383 | 0.5789 |
0.3286 | 13.0 | 1547 | 1.6635 | 0.5811 |
0.3286 | 14.0 | 1666 | 1.7684 | 0.5621 |
0.3286 | 15.0 | 1785 | 1.8133 | 0.5684 |
0.3286 | 16.0 | 1904 | 1.8770 | 0.5705 |
0.1571 | 17.0 | 2023 | 1.8929 | 0.5916 |
0.1571 | 18.0 | 2142 | 1.9210 | 0.5811 |
0.1571 | 19.0 | 2261 | 1.9451 | 0.5895 |
0.1571 | 20.0 | 2380 | 2.0018 | 0.5726 |
0.1571 | 21.0 | 2499 | 1.9992 | 0.5768 |
0.0924 | 22.0 | 2618 | 2.0863 | 0.5768 |
0.0924 | 23.0 | 2737 | 2.1038 | 0.5811 |
0.0924 | 24.0 | 2856 | 2.1313 | 0.5747 |
0.0924 | 25.0 | 2975 | 2.1055 | 0.5726 |
0.0752 | 26.0 | 3094 | 2.1162 | 0.5705 |
0.0752 | 27.0 | 3213 | 2.1612 | 0.5705 |
0.0752 | 28.0 | 3332 | 2.1885 | 0.5768 |
0.0752 | 29.0 | 3451 | 2.1585 | 0.5642 |
0.0616 | 30.0 | 3570 | 2.2013 | 0.5768 |
0.0616 | 31.0 | 3689 | 2.1932 | 0.5768 |
0.0616 | 32.0 | 3808 | 2.2058 | 0.5726 |
0.0616 | 33.0 | 3927 | 2.2331 | 0.5705 |
0.0583 | 34.0 | 4046 | 2.2470 | 0.5663 |
0.0583 | 35.0 | 4165 | 2.2558 | 0.5747 |
0.0583 | 36.0 | 4284 | 2.2560 | 0.5747 |
0.0583 | 37.0 | 4403 | 2.2577 | 0.5768 |
0.0483 | 38.0 | 4522 | 2.2817 | 0.5726 |
0.0483 | 39.0 | 4641 | 2.2795 | 0.5789 |
0.0483 | 40.0 | 4760 | 2.2845 | 0.5811 |
0.0483 | 41.0 | 4879 | 2.3065 | 0.5789 |
0.0483 | 42.0 | 4998 | 2.3018 | 0.5747 |
0.0474 | 43.0 | 5117 | 2.3147 | 0.5789 |
0.0474 | 44.0 | 5236 | 2.3279 | 0.5768 |
0.0474 | 45.0 | 5355 | 2.3330 | 0.5768 |
0.0474 | 46.0 | 5474 | 2.3449 | 0.5726 |
0.0422 | 47.0 | 5593 | 2.3433 | 0.5789 |
0.0422 | 48.0 | 5712 | 2.3418 | 0.5726 |
0.0422 | 49.0 | 5831 | 2.3411 | 0.5747 |
0.0422 | 50.0 | 5950 | 2.3403 | 0.5726 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for Mukalingam0813/brand-safety-classifier
Base model
distilbert/distilbert-base-uncased