Downloads · 30 days
8
5% of all-time downloads
N_bert_agnews_padding0model
Realgon/N_bert_agnews_padding0model
N_bert_agnews_padding0model 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
166
Public
Repo size
9.2 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin438 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Dec 27, 2023
- Updated
- Dec 27, 2023
- SHA
- d97de7d8
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_bert_agnews_padding0model
This model is a fine-tuned version of bert-base-uncased on the ag_news dataset. It achieves the following results on the evaluation set:
- Loss: 0.5653
- Accuracy: 0.9476
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 |
|---|---|---|---|---|
| 0.1773 | 1.0 | 7500 | 0.1841 | 0.9433 |
| 0.1354 | 2.0 | 15000 | 0.2061 | 0.9463 |
| 0.1138 | 3.0 | 22500 | 0.2455 | 0.9428 |
| 0.0852 | 4.0 | 30000 | 0.2881 | 0.9429 |
| 0.0627 | 5.0 | 37500 | 0.3271 | 0.9433 |
| 0.0436 | 6.0 | 45000 | 0.3524 | 0.9441 |
| 0.034 | 7.0 | 52500 | 0.3977 | 0.9424 |
| 0.0251 | 8.0 | 60000 | 0.4291 | 0.9441 |
| 0.0205 | 9.0 | 67500 | 0.4399 | 0.9420 |
| 0.0167 | 10.0 | 75000 | 0.4574 | 0.9429 |
| 0.0218 | 11.0 | 82500 | 0.4979 | 0.9429 |
| 0.0119 | 12.0 | 90000 | 0.5000 | 0.9438 |
| 0.0112 | 13.0 | 97500 | 0.4856 | 0.9454 |
| 0.0054 | 14.0 | 105000 | 0.5294 | 0.9457 |
| 0.0039 | 15.0 | 112500 | 0.5418 | 0.9459 |
| 0.0024 | 16.0 | 120000 | 0.5065 | 0.9468 |
| 0.0011 | 17.0 | 127500 | 0.5511 | 0.9458 |
| 0.0013 | 18.0 | 135000 | 0.5411 | 0.9471 |
| 0.0002 | 19.0 | 142500 | 0.5555 | 0.9472 |
| 0.0005 | 20.0 | 150000 | 0.5653 | 0.9476 |
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
- bert
- License
- apache-2.0
- Created
- Dec 27, 2023
- Updated
- Dec 27, 2023