Downloads · 30 days
13
6% of all-time downloads
N_roberta_agnews_padding50model
Realgon/N_roberta_agnews_padding50model
N_roberta_agnews_padding50model is a text classification model from Realgon. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
219
Public
Repo size
10.5 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin499 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Dec 25, 2023
- Updated
- Dec 26, 2023
- SHA
- 2be04f71
Try a prompt
Base models
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
N_roberta_agnews_padding50model
This model is a fine-tuned version of roberta-base on the ag_news dataset. It achieves the following results on the evaluation set:
- Loss: 0.5524
- Accuracy: 0.9486
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: 16
- eval_batch_size: 16
- 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 | Accuracy |
|---|---|---|---|---|
| 0.1998 | 1.0 | 7500 | 0.2132 | 0.9382 |
| 0.1682 | 2.0 | 15000 | 0.2009 | 0.9475 |
| 0.1506 | 3.0 | 22500 | 0.2273 | 0.9446 |
| 0.1294 | 4.0 | 30000 | 0.2495 | 0.9482 |
| 0.1028 | 5.0 | 37500 | 0.2612 | 0.9459 |
| 0.0797 | 6.0 | 45000 | 0.2966 | 0.9457 |
| 0.0646 | 7.0 | 52500 | 0.3040 | 0.9458 |
| 0.0531 | 8.0 | 60000 | 0.3825 | 0.9446 |
| 0.0443 | 9.0 | 67500 | 0.3838 | 0.9425 |
| 0.0345 | 10.0 | 75000 | 0.3968 | 0.9475 |
| 0.0395 | 11.0 | 82500 | 0.4132 | 0.9474 |
| 0.019 | 12.0 | 90000 | 0.4612 | 0.9453 |
| 0.0219 | 13.0 | 97500 | 0.4559 | 0.9458 |
| 0.0067 | 14.0 | 105000 | 0.4692 | 0.9467 |
| 0.0065 | 15.0 | 112500 | 0.5118 | 0.9461 |
| 0.0045 | 16.0 | 120000 | 0.5115 | 0.9470 |
| 0.004 | 17.0 | 127500 | 0.5326 | 0.9472 |
| 0.0079 | 18.0 | 135000 | 0.5088 | 0.9483 |
| 0.0039 | 19.0 | 142500 | 0.5359 | 0.9504 |
| 0.0024 | 20.0 | 150000 | 0.5524 | 0.9486 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Dec 25, 2023
- Updated
- Dec 26, 2023