Downloads · 30 days
6
2% of all-time downloads
bert-base-arabic-emotion-analysis-v3
alpcansoydas/bert-base-arabic-emotion-analysis-v3
bert-base-arabic-emotion-analysis-v3 is a text classification model from alpcansoydas. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
389
Public
Parameters
111M
443 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors443 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Nov 21, 2023
- Updated
- Nov 21, 2023
- SHA
- a3cb2cc3
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-arabic-emotion-analysis-v3
This model is a fine-tuned version of asafaya/bert-base-arabic on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5940
- Accuracy: 0.7928
- F1: 0.7932
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.9993 | 1.0 | 102 | 0.6655 | 0.7528 | 0.7510 |
| 0.5781 | 2.0 | 204 | 0.6018 | 0.7721 | 0.7720 |
| 0.4441 | 3.0 | 306 | 0.5940 | 0.7928 | 0.7932 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Nov 21, 2023
- Updated
- Nov 21, 2023