takala/financial_phrasebank
The key arguments for the low utilization of statistical techniques in financial sentiment analysis have been the difficulty of implementation for practical applications and the lack of high quality training data for building such models. Especially in the case of finance and economic texts, annotated collections are a scarce resource and many are reserved for proprietary use only. To resolve the missing training data problem, we present a collection of ∼ 5000 sentences to establish human-annotated standards for benchmarking alternative modeling techniques. The objective of the phrase level an
| Author / organization | takala |
|---|---|
| License (as declared) | cc-by-nc-sa-3.0 |
| Downloads | 9.1K (as reported by Hugging Face) |
| Likes | 287 |
| Created | 2 March 2022 |
| Last updated at source | 15 December 2025 |
Popularity, last 3 days
9,059 now (+1,069 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- AnkitAI/FinSense-ModernBERT-Financial-News-Sentiment-AnalysisModel · used to train
- beethogedeon/UltraFinBERT-150MModel · used to train
- mradermacher/WORLD_ARCHIVES_II-GGUFModel · used to train
- 9mark9/finbert-minilm-sentimentModel · used to train
- beethogedeon/Modern-FinBERT-largeModel · used to train
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.