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: 1.2512
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 |
|---|---|---|---|
| 2.1019 | 1.0 | 291 | 1.7019 |
| 1.6412 | 2.0 | 582 | 1.4273 |
| 1.4844 | 3.0 | 873 | 1.3947 |
| 1.4006 | 4.0 | 1164 | 1.3698 |
| 1.3382 | 5.0 | 1455 | 1.1941 |
| 1.2822 | 6.0 | 1746 | 1.2781 |
| 1.2393 | 7.0 | 2037 | 1.2650 |
| 1.2009 | 8.0 | 2328 | 1.2082 |
| 1.1657 | 9.0 | 2619 | 1.1776 |
| 1.1394 | 10.0 | 2910 | 1.2050 |
| 1.1276 | 11.0 | 3201 | 1.2067 |
| 1.1051 | 12.0 | 3492 | 1.1630 |
| 1.0814 | 13.0 | 3783 | 1.2529 |
| 1.0757 | 14.0 | 4074 | 1.1699 |
| 1.063 | 15.0 | 4365 | 1.1113 |
| 1.0637 | 16.0 | 4656 | 1.2512 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.11.0+cu113
- Datasets 1.16.1
- Tokenizers 0.10.1
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Model tree for jmassot/bert-base-uncased-issues-128
Base model
google-bert/bert-base-uncased