takala/financial_phrasebank
Updated β’ 8.54k β’ 259
How to use OMCHOKSI108/FineStream with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="OMCHOKSI108/FineStream") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("OMCHOKSI108/FineStream")
model = AutoModelForSequenceClassification.from_pretrained("OMCHOKSI108/FineStream")Fine-tuned
distilroberta-basefor 3-class financial sentiment classification. Part of the FinStream active learning pipeline.
FinStream is a DistilRoBERTa-base model fine-tuned on the Financial PhraseBank dataset
(sentences_allagree subset) to classify financial news into three sentiment classes:
| Label | ID | Meaning |
|---|---|---|
| π» bearish | 0 | Negative market outlook |
| π neutral | 1 | No strong directional signal |
| π bullish | 2 | Positive market outlook |
| Metric | Score |
|---|---|
| Test Accuracy | 0.8680 |
| Training Set | Financial PhraseBank (all_agree) |
from transformers import pipeline
classifier = pipeline(
'text-classification',
model='OMCHOKSI108/FinStream',
)
result = classifier("Federal Reserve signals interest rate cuts.")
print(result) # [{'label': 'bullish', 'score': 0.94}]
distilroberta-basesentences_allagree)|OM Choksi
Built as part of the FinStream Active Learning Pipeline β a portfolio-grade financial NLP project.