---
library_name: transformers
license: mit
base_model: ihsan31415/indo-roBERTa-financial-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: stockbit-sentiment
  results: []
---

<!-- 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. -->

# stockbit-sentiment

This model is a fine-tuned version of [ihsan31415/indo-roBERTa-financial-sentiment](https://huggingface.co/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