EomaxlSam
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finbert-finetuned-sentimentpulse

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 ---
+language: en
+license: apache-2.0
+tags:
+  - financial-sentiment
+  - finbert
+  - text-classification
+  - finance
+datasets:
+  - financial_phrasebank
+  - pauri32/fiqa-2018
+base_model: ProsusAI/finbert
+metrics:
+  - f1
 ---
+# finbert-finetuned-sentimentpulse
+Fine-tuned [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) for 3-class financial news sentiment classification (positive / negative / neutral).
+Part of the [SentimentPulse](https://github.com/Eomaxl/SentimentPulse) pipeline — an open-source replica of Bloomberg BQuant Textual Analytics.
+## Benchmark
+Evaluated on 349 held-out examples from FinancialPhraseBank + FiQA-SA:
+| Model | Precision | Recall | F1 |
+|---|---|---|---|
+| VADER | 0.52 | 0.48 | 0.51 |
+| Loughran-McDonald | 0.64 | 0.47 | 0.47 |
+| FinBERT zero-shot | 0.79 | 0.75 | 0.76 |
+| **FinBERT fine-tuned (this model)** | **0.92** | **0.92** | **0.92** |
+Per-class (fine-tuned):
+| Class | Precision | Recall | F1 | Support |
+|---|---|---|---|---|
+| negative | 0.83 | 0.86 | 0.85 | 74 |
+| neutral | 0.99 | 0.98 | 0.99 | 140 |
+| positive | 0.90 | 0.90 | 0.90 | 135 |
+## Training
+- **Base model:** ProsusAI/finbert
+- **Training data:** FinancialPhraseBank (`sentences_allagree`, 2,264 sentences) + FiQA-SA (`pauri32/fiqa-2018`, 1,173 sentences) — 80/10/10 stratified split
+- **Epochs:** 5 · **Batch size:** 16 · **LR:** 2e-5 · **WeightedTrainer** (inverse class frequency)
+- **Hardware:** Apple MPS (~4.5 min)
+- **Framework:** HuggingFace Transformers 4.41
+## Usage
+```python
+from transformers import pipeline
+pipe = pipeline(
+    "text-classification",
+    model="EomaxlSam/finbert-finetuned-sentimentpulse",
+)
+pipe("Apple beats Q1 earnings estimates by 12%")
+# [{'label': 'positive', 'score': 0.94}]
+pipe("Goldman Sachs fell sharply after issuing a guidance cut.")
+# [{'label': 'negative', 'score': 0.91}]
+```
+## Labels
+| ID | Label |
+|---|---|
+| 0 | negative |
+| 1 | neutral |
+| 2 | positive |
+## Repository
+[github.com/Eomaxl/SentimentPulse](https://github.com/Eomaxl/SentimentPulse)