bert-base-uncased-dietdupe-foodb-desc
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6188
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 124 | 1.6109 |
| No log | 2.0 | 248 | 1.6449 |
| No log | 3.0 | 372 | 1.7693 |
| No log | 4.0 | 496 | 1.7404 |
| 1.8504 | 5.0 | 620 | 1.6661 |
| 1.8504 | 6.0 | 744 | 1.5235 |
| 1.8504 | 7.0 | 868 | 1.5884 |
| 1.8504 | 8.0 | 992 | 1.6669 |
| 1.6616 | 9.0 | 1116 | 1.4289 |
| 1.6616 | 10.0 | 1240 | 1.6314 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1
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Model tree for ja-nina/bert-base-uncased-dietdupe-foodb-desc
Base model
google-bert/bert-base-uncased