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: 1.2430
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1051 | 1.0 | 291 | 1.6955 |
| 1.6311 | 2.0 | 582 | 1.5132 |
| 1.4968 | 3.0 | 873 | 1.3491 |
| 1.394 | 4.0 | 1164 | 1.3301 |
| 1.3309 | 5.0 | 1455 | 1.2343 |
| 1.2833 | 6.0 | 1746 | 1.3496 |
| 1.2305 | 7.0 | 2037 | 1.2995 |
| 1.2018 | 8.0 | 2328 | 1.3417 |
| 1.1667 | 9.0 | 2619 | 1.2182 |
| 1.1388 | 10.0 | 2910 | 1.1757 |
| 1.1281 | 11.0 | 3201 | 1.1448 |
| 1.1094 | 12.0 | 3492 | 1.1833 |
| 1.0896 | 13.0 | 3783 | 1.2279 |
| 1.0761 | 14.0 | 4074 | 1.2065 |
| 1.0718 | 15.0 | 4365 | 1.2319 |
| 1.0644 | 16.0 | 4656 | 1.2430 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for smoxi/bert-base-uncased-issues-128
Base model
google-bert/bert-base-uncased