Text Classification
Transformers
Safetensors
English
ultrabert
finance
sentiment-analysis
financial-sentiment-analysis
custom_code
fp16
Eval Results (legacy)
Instructions to use beethogedeon/UltraFinBERT-150M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beethogedeon/UltraFinBERT-150M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="beethogedeon/UltraFinBERT-150M", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("beethogedeon/UltraFinBERT-150M", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("beethogedeon/UltraFinBERT-150M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download ProsusAI__finbert_classification_report.json from beethogedeon/UltraFinBERT-150M: direct link, hf CLI and curl.
- Browser
- Download file 752 Bytes
-
https://huggingface.co/beethogedeon/UltraFinBERT-150M/resolve/main/ProsusAI__finbert_classification_report.json
- Command line
-
hf download hf://beethogedeon/UltraFinBERT-150M/ProsusAI__finbert_classification_report.json
-
curl -L -o ProsusAI__finbert_classification_report.json https://huggingface.co/beethogedeon/UltraFinBERT-150M/resolve/main/ProsusAI__finbert_classification_report.json
752 Bytes
| { | |
| "negative": { | |
| "precision": 0.9574468085106383, | |
| "recall": 0.9782608695652174, | |
| "f1-score": 0.967741935483871, | |
| "support": 46.0 | |
| }, | |
| "neutral": { | |
| "precision": 1.0, | |
| "recall": 0.9759615384615384, | |
| "f1-score": 0.9878345498783455, | |
| "support": 208.0 | |
| }, | |
| "positive": { | |
| "precision": 0.9550561797752809, | |
| "recall": 1.0, | |
| "f1-score": 0.9770114942528736, | |
| "support": 85.0 | |
| }, | |
| "accuracy": 0.9823008849557522, | |
| "macro avg": { | |
| "precision": 0.9708343294286398, | |
| "recall": 0.9847408026755854, | |
| "f1-score": 0.9775293265383634, | |
| "support": 339.0 | |
| }, | |
| "weighted avg": { | |
| "precision": 0.9829567211574874, | |
| "recall": 0.9823008849557522, | |
| "f1-score": 0.9823943729157764, | |
| "support": 339.0 | |
| } | |
| } |