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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-issues-128
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-uncased-issues-128
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GitHub issues dataset. The model is used in Chapter 9: Dealing with Few to No Labels in the [NLP with Transformers book](https://learning.oreilly.com/library/view/natural-language-processing/9781098103231/). You can find the full code in the accompanying [Github repository](https://github.com/nlp-with-transformers/notebooks/blob/main/09_few-to-no-labels.ipynb).
It achieves the following results on the evaluation set:
- Loss: 1.2520
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0949 | 1.0 | 291 | 1.7072 |
| 1.649 | 2.0 | 582 | 1.4409 |
| 1.4835 | 3.0 | 873 | 1.4099 |
| 1.3938 | 4.0 | 1164 | 1.3858 |
| 1.3326 | 5.0 | 1455 | 1.2004 |
| 1.2949 | 6.0 | 1746 | 1.2955 |
| 1.2451 | 7.0 | 2037 | 1.2682 |
| 1.1992 | 8.0 | 2328 | 1.1938 |
| 1.1784 | 9.0 | 2619 | 1.1686 |
| 1.1397 | 10.0 | 2910 | 1.2050 |
| 1.1293 | 11.0 | 3201 | 1.2058 |
| 1.1006 | 12.0 | 3492 | 1.1680 |
| 1.0835 | 13.0 | 3783 | 1.2414 |
| 1.0757 | 14.0 | 4074 | 1.1522 |
| 1.062 | 15.0 | 4365 | 1.1176 |
| 1.0535 | 16.0 | 4656 | 1.2520 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu102
- Datasets 1.13.0
- Tokenizers 0.10.3
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