gbert-base-finetuned-twitter_
This model is a fine-tuned version of deepset/gbert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6651
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: 2e-05
- train_batch_size: 192
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1933 | 1.0 | 4180 | 1.9612 |
| 2.0051 | 2.0 | 8360 | 1.8795 |
| 1.939 | 3.0 | 12540 | 1.8310 |
| 1.8928 | 4.0 | 16720 | 1.8013 |
| 1.8594 | 5.0 | 20900 | 1.7730 |
| 1.8336 | 6.0 | 25080 | 1.7702 |
| 1.8145 | 7.0 | 29260 | 1.7449 |
| 1.7963 | 8.0 | 33440 | 1.7277 |
| 1.7806 | 9.0 | 37620 | 1.7105 |
| 1.7682 | 10.0 | 41800 | 1.7061 |
| 1.7584 | 11.0 | 45980 | 1.7041 |
| 1.7454 | 12.0 | 50160 | 1.6899 |
| 1.7374 | 13.0 | 54340 | 1.6850 |
| 1.7295 | 14.0 | 58520 | 1.6856 |
| 1.7232 | 15.0 | 62700 | 1.6819 |
| 1.715 | 16.0 | 66880 | 1.6730 |
| 1.7101 | 17.0 | 71060 | 1.6723 |
| 1.7057 | 18.0 | 75240 | 1.6655 |
| 1.7038 | 19.0 | 79420 | 1.6617 |
| 1.702 | 20.0 | 83600 | 1.6625 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for JanSt/gbert-base-finetuned-twitter_
Base model
deepset/gbert-base