Tradepulse Finbert Sentiment

--- language: en license: apache-2.0 tags: - finance - sentiment-analysis - finbert - trading pipeline_tag: text-classification --- # Bencode92/tradepulse-finbert-sentiment ## Description Fine-tuned FinBERT model for financial sentiment analysis in TradePulse. **Task**: Sentiment Classification **Target Column**: `label` **Labels**: ['negative', 'neutral', 'positive'] ## Performance *Last training: 2026-04-20 17:22* *Dataset: `base_reference.csv` (1797 samples)* | Metric | Value | |--------|-------| | Loss | 0.0000 | | Accuracy | 1.0000 | | F1 Score | 1.0000 | | F1 Macro | 1.0000 | | Precision | 1.0000 | | Recall | 1.0000 | ## Training Details - **Base Model**: Bencode92/tradepulse-finbert-sentiment - **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-sentiment") model = AutoModelForSequenceClassification.from_pretrained("Bencode92/tradepulse-finbert-sentiment") # 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 2026-04-20 17:22:25