|
|
--- |
|
|
language: en |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- finance |
|
|
- sentiment-analysis |
|
|
- finbert |
|
|
- trading |
|
|
|
|
|
pipeline_tag: text-classification |
|
|
--- |
|
|
|
|
|
# Bencode92/tradepulse-finbert-importance |
|
|
|
|
|
## Description |
|
|
Fine-tuned FinBERT model for financial importance analysis in TradePulse. |
|
|
|
|
|
**Task**: Importance Classification |
|
|
**Target Column**: `importance` |
|
|
**Labels**: ['générale', 'importante', 'critique'] |
|
|
|
|
|
## Performance |
|
|
|
|
|
*Last training: 2025-09-09 16:49* |
|
|
*Dataset: `base_reference.csv` (1797 samples)* |
|
|
|
|
|
| Metric | Value | |
|
|
|--------|-------| |
|
|
| Loss | 0.6364 | |
|
|
| Accuracy | 0.8044 | |
|
|
| F1 Score | 0.7994 | |
|
|
|
|
|
| F1 Macro | 0.7994 | |
|
|
|
|
|
| Precision | 0.7989 | |
|
|
| Recall | 0.8044 | |
|
|
|
|
|
## Training Details |
|
|
|
|
|
- **Base Model**: Bencode92/tradepulse-finbert-importance |
|
|
- **Training Mode**: Incremental |
|
|
- **Epochs**: 2 |
|
|
- **Learning Rate**: 1e-05 |
|
|
- **Batch Size**: 4 |
|
|
- **Class Balancing**: None |
|
|
|
|
|
|
|
|
## Usage |
|
|
|
|
|
```python |
|
|
from transformers import AutoTokenizer, AutoModelForSequenceClassification |
|
|
import torch |
|
|
|
|
|
tokenizer = AutoTokenizer.from_pretrained("Bencode92/tradepulse-finbert-importance") |
|
|
model = AutoModelForSequenceClassification.from_pretrained("Bencode92/tradepulse-finbert-importance") |
|
|
|
|
|
# Example prediction |
|
|
text = "Apple reported strong quarterly earnings beating expectations" |
|
|
inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True) |
|
|
outputs = model(**inputs) |
|
|
|
|
|
predictions = outputs.logits.softmax(dim=-1) |
|
|
``` |
|
|
|
|
|
## Model Card Authors |
|
|
|
|
|
- TradePulse ML Team |
|
|
- Auto-generated on 2025-09-09 16:49:13 |
