Downloads · 30 days
6
10% of all-time downloads
bert-base-uncased-supreme-court-32batch_5epoch_2e5lr_01wd
annabellehuether/bert-base-uncased-supreme-court-32batch_5epoch_2e5lr_01wd
bert-base-uncased-supreme-court-32batch_5epoch_2e5lr_01wd is a text classification model from annabellehuether. 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
61
Public
Parameters
109M
3.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors438 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Dec 3, 2023
- Updated
- Dec 3, 2023
- SHA
- e909aad5
Try a prompt
Base models
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. -->
bert-base-uncased-supreme-court-32batch_5epoch_2e5lr_01wd
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: 0.8422
- Accuracy: 0.6533
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: 32
- eval_batch_size: 32
- seed: 7
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6444 | 1.0 | 660 | 0.5548 | 0.6456 |
| 0.6056 | 2.0 | 1320 | 0.5561 | 0.6626 |
| 0.5633 | 3.0 | 1980 | 0.6407 | 0.6448 |
| 0.4092 | 4.0 | 2640 | 0.7330 | 0.6493 |
| 0.3395 | 5.0 | 3300 | 0.8422 | 0.6533 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Dec 3, 2023
- Updated
- Dec 3, 2023