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: 1.0940
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 |
|---|---|---|---|
| 2.1003 | 1.0 | 291 | 1.6578 |
| 1.6211 | 2.0 | 582 | 1.4140 |
| 1.4964 | 3.0 | 873 | 1.3040 |
| 1.41 | 4.0 | 1164 | 1.3011 |
| 1.336 | 5.0 | 1455 | 1.3095 |
| 1.2862 | 6.0 | 1746 | 1.3739 |
| 1.2271 | 7.0 | 2037 | 1.2743 |
| 1.2043 | 8.0 | 2328 | 1.2019 |
| 1.1701 | 9.0 | 2619 | 1.2696 |
| 1.1498 | 10.0 | 2910 | 1.2507 |
| 1.1194 | 11.0 | 3201 | 1.1398 |
| 1.1094 | 12.0 | 3492 | 1.1309 |
| 1.0913 | 13.0 | 3783 | 1.0740 |
| 1.0683 | 14.0 | 4074 | 1.1201 |
| 1.0607 | 15.0 | 4365 | 1.1690 |
| 1.0558 | 16.0 | 4656 | 1.0940 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.12.1
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Model tree for susnato/bert-base-uncased-issues-128
Base model
google-bert/bert-base-uncased