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: 1.2353
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 |
|---|---|---|---|
| 2.0991 | 1.0 | 291 | 1.7002 |
| 1.6295 | 2.0 | 582 | 1.5208 |
| 1.4967 | 3.0 | 873 | 1.3521 |
| 1.3965 | 4.0 | 1164 | 1.3367 |
| 1.332 | 5.0 | 1455 | 1.2266 |
| 1.285 | 6.0 | 1746 | 1.3645 |
| 1.2314 | 7.0 | 2037 | 1.2992 |
| 1.2027 | 8.0 | 2328 | 1.3514 |
| 1.1688 | 9.0 | 2619 | 1.2146 |
| 1.1407 | 10.0 | 2910 | 1.1802 |
| 1.1272 | 11.0 | 3201 | 1.1346 |
| 1.1131 | 12.0 | 3492 | 1.1902 |
| 1.0892 | 13.0 | 3783 | 1.2254 |
| 1.0755 | 14.0 | 4074 | 1.2124 |
| 1.0741 | 15.0 | 4365 | 1.2180 |
| 1.0604 | 16.0 | 4656 | 1.2353 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for khalidr/bert-base-uncased-issues-128
Base model
google-bert/bert-base-uncased