Downloads · 30 days
15
12% of all-time downloads
ternary_persian_sentiment_analysis
rezaFarsh/ternary_persian_sentiment_analysis
ternary_persian_sentiment_analysis is a text classification model from rezaFarsh. 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
125
Public
Parameters
471M
65.9 GB on disk
Likes
1
Public
Repo makeup
Click a slice to open those files.
.safetensors1.9 GB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Jan 22, 2024
- Updated
- Jan 23, 2024
- SHA
- 828ecf22
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. -->
ternary_persian_sentiment_analysis
This model is a fine-tuned version of sentence-transformers/LaBSE on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4914
- Accuracy: 0.8458
- F1 Score: 0.8459
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | F1 Score |
|---|---|---|---|---|---|
| 0.496 | 1.0 | 1394 | 0.4708 | 0.8192 | 0.8186 |
| 0.4177 | 2.0 | 2788 | 0.4914 | 0.8458 | 0.8459 |
| 0.3237 | 3.0 | 4182 | 0.5736 | 0.8354 | 0.8356 |
| 0.2874 | 4.0 | 5576 | 0.7309 | 0.8216 | 0.8217 |
| 0.2142 | 5.0 | 6970 | 0.9256 | 0.8184 | 0.8187 |
| 0.1494 | 6.0 | 8364 | 1.0608 | 0.8200 | 0.8197 |
| 0.1396 | 7.0 | 9758 | 1.0638 | 0.8257 | 0.8256 |
| 0.0983 | 8.0 | 11152 | 1.2088 | 0.8200 | 0.8200 |
| 0.0907 | 9.0 | 12546 | 1.3653 | 0.8079 | 0.8083 |
| 0.0727 | 10.0 | 13940 | 1.3032 | 0.8305 | 0.8307 |
| 0.0526 | 11.0 | 15334 | 1.4689 | 0.8184 | 0.8184 |
| 0.0413 | 12.0 | 16728 | 1.4875 | 0.8224 | 0.8227 |
| 0.0265 | 13.0 | 18122 | 1.6185 | 0.8241 | 0.8242 |
| 0.0366 | 14.0 | 19516 | 1.7135 | 0.8168 | 0.8168 |
| 0.0251 | 15.0 | 20910 | 1.6607 | 0.8249 | 0.8251 |
| 0.0151 | 16.0 | 22304 | 1.7922 | 0.8111 | 0.8111 |
| 0.0159 | 17.0 | 23698 | 1.7303 | 0.8200 | 0.8201 |
| 0.0163 | 18.0 | 25092 | 1.7555 | 0.8232 | 0.8232 |
| 0.0178 | 19.0 | 26486 | 1.7680 | 0.8232 | 0.8232 |
| 0.0147 | 20.0 | 27880 | 1.7546 | 0.8216 | 0.8217 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jan 22, 2024
- Updated
- Jan 23, 2024