Downloads · 30 days
5
10% of all-time downloads
Qt20ALBERT_Unbalance
YakovElm/Qt20ALBERT_Unbalance
Qt20ALBERT_Unbalance is a text classification model from YakovElm. 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.
probably proofread and complete it, then remove this comment. --
All-time downloads
50
Public
Repo size
46.8 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.h546.8 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- albert
- Access
- Public
- Created
- May 25, 2023
- Updated
- May 25, 2023
- SHA
- bb80e4f6
Try a prompt
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
Qt20ALBERT_Unbalance
This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1378
- Train Accuracy: 0.9559
- Validation Loss: 0.2005
- Validation Accuracy: 0.9359
- Epoch: 9
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:
- optimizer: {'name': 'Adam', 'weight_decay': 0.001, 'clipnorm': 1.0, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 3e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|---|---|---|---|---|
| 0.2122 | 0.9454 | 0.1637 | 0.9586 | 0 |
| 0.2095 | 0.9462 | 0.1649 | 0.9586 | 1 |
| 0.2104 | 0.9462 | 0.1704 | 0.9586 | 2 |
| 0.2064 | 0.9462 | 0.1593 | 0.9586 | 3 |
| 0.1982 | 0.9462 | 0.1824 | 0.9586 | 4 |
| 0.2003 | 0.9462 | 0.1635 | 0.9586 | 5 |
| 0.1947 | 0.9456 | 0.1591 | 0.9586 | 6 |
| 0.1852 | 0.9459 | 0.1772 | 0.9586 | 7 |
| 0.1650 | 0.9467 | 0.1982 | 0.9586 | 8 |
| 0.1378 | 0.9559 | 0.2005 | 0.9359 | 9 |
Framework versions
- Transformers 4.29.2
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- albert
- License
- apache-2.0
- Created
- May 25, 2023
- Updated
- May 25, 2023