Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use will702/stockbit-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use will702/stockbit-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="will702/stockbit-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("will702/stockbit-sentiment") model = AutoModelForSequenceClassification.from_pretrained("will702/stockbit-sentiment") - Notebooks
- Google Colab
- Kaggle
stockbit-sentiment
This model is a fine-tuned version of ihsan31415/indo-roBERTa-financial-sentiment on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3053
- Accuracy: 0.8867
- Precision Weighted: 0.8872
- Recall Weighted: 0.8867
- F1 Weighted: 0.8860
- F1 Macro: 0.8787
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Weighted | Recall Weighted | F1 Weighted | F1 Macro |
|---|---|---|---|---|---|---|---|---|
| 0.313 | 1.0 | 1350 | 0.3053 | 0.8867 | 0.8872 | 0.8867 | 0.8860 | 0.8787 |
| 0.1959 | 2.0 | 2700 | 0.3629 | 0.8961 | 0.8987 | 0.8961 | 0.8957 | 0.8858 |
| 0.1037 | 3.0 | 4050 | 0.4347 | 0.9087 | 0.9083 | 0.9087 | 0.9084 | 0.9010 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.8.0+cu128
- Datasets 4.4.1
- Tokenizers 0.22.2
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Model tree for will702/stockbit-sentiment
Base model
ihsan31415/indo-roBERTa-financial-sentiment