Downloads · 30 days
13
3% of all-time downloads
arabert-large-finetuned-sentiment-analysis
AlyGreo/arabert-large-finetuned-sentiment-analysis
arabert-large-finetuned-sentiment-analysis is a text classification model from AlyGreo. 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
387
Public
Parameters
135M
541 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors541 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 28, 2024
- Updated
- Mar 28, 2024
- SHA
- 750309eb
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. -->
arabert-large-finetuned-sentiment-analysis
This model is a fine-tuned version of aubmindlab/bert-base-arabertv2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7905
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: 0.0002
- 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
- training_steps: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9166 | 0.0 | 2 | 0.6761 |
| 0.628 | 0.01 | 4 | 0.6767 |
| 0.6367 | 0.01 | 6 | 0.6816 |
| 0.6504 | 0.02 | 8 | 0.7792 |
| 0.6936 | 0.02 | 10 | 0.7905 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Mar 28, 2024
- Updated
- Mar 28, 2024