Downloads · 30 days
10
32% of all-time downloads
CPALL-Stock-Trend-Prediction-category-filter-Wangchanberta-APR
jab11769/CPALL-Stock-Trend-Prediction-category-filter-Wangchanberta-APR
CPALL-Stock-Trend-Prediction-category-filter-Wangchanberta-APR is a text classification model from jab11769. 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
31
Public
Parameters
105M
422 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors421 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- camembert
- Access
- Public
- Created
- Apr 19, 2025
- Updated
- Apr 19, 2025
- SHA
- c726a522
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. -->
CPALL-Stock-Trend-Prediction-category-filter-Wangchanberta-APR
This model is a fine-tuned version of airesearch/wangchanberta-base-att-spm-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0950
- Accuracy: 0.4635
- Precision: 0.2149
- Recall: 0.4635
- F1: 0.2936
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.1227 | 1.0 | 548 | 1.1233 | 0.3241 | 0.3829 | 0.3241 | 0.3005 |
| 1.1154 | 2.0 | 1096 | 1.0935 | 0.3739 | 0.3871 | 0.3739 | 0.3790 |
| 1.1113 | 3.0 | 1644 | 1.1018 | 0.4633 | 0.2148 | 0.4633 | 0.2936 |
| 1.1073 | 4.0 | 2192 | 1.0677 | 0.3397 | 0.1154 | 0.3397 | 0.1723 |
| 1.1076 | 5.0 | 2740 | 1.0728 | 0.4635 | 0.2149 | 0.4635 | 0.2936 |
| 1.1061 | 6.0 | 3288 | 1.1124 | 0.3397 | 0.1154 | 0.3397 | 0.1723 |
| 1.104 | 7.0 | 3836 | 1.1173 | 0.1968 | 0.0387 | 0.1968 | 0.0647 |
| 1.1059 | 8.0 | 4384 | 1.1117 | 0.3397 | 0.1154 | 0.3397 | 0.1723 |
| 1.1033 | 9.0 | 4932 | 1.0900 | 0.4635 | 0.2149 | 0.4635 | 0.2936 |
| 1.1059 | 10.0 | 5480 | 1.0950 | 0.4635 | 0.2149 | 0.4635 | 0.2936 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
- Task
- Text Classification
- Library
- transformers
- Type
- camembert
- Created
- Apr 19, 2025
- Updated
- Apr 19, 2025