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bert-base-uncased-issues-128
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: 1.1883
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1094 | 1.0 | 291 | 1.6856 |
| 1.6364 | 2.0 | 582 | 1.3676 |
| 1.4818 | 3.0 | 873 | 1.4158 |
| 1.397 | 4.0 | 1164 | 1.4260 |
| 1.3407 | 5.0 | 1455 | 1.2725 |
| 1.2883 | 6.0 | 1746 | 1.3102 |
| 1.2308 | 7.0 | 2037 | 1.2178 |
| 1.2122 | 8.0 | 2328 | 1.2875 |
| 1.179 | 9.0 | 2619 | 1.2713 |
| 1.1501 | 10.0 | 2910 | 1.2187 |
| 1.1253 | 11.0 | 3201 | 1.2641 |
| 1.0996 | 12.0 | 3492 | 1.1546 |
| 1.0925 | 13.0 | 3783 | 1.1543 |
| 1.077 | 14.0 | 4074 | 1.0697 |
| 1.0653 | 15.0 | 4365 | 1.2503 |
| 1.0676 | 16.0 | 4656 | 1.1883 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
