Model info
- Base model: Llama2-7B
- Training method: Instruction Fine-tuning + LoRA
- Task: Multi-Task
Packages
!pip install transformers==4.32.0 peft==0.5.0
!pip install sentencepiece
!pip install accelerate
!pip install torch
!pip install peft
!pip install datasets
!pip install bitsandbytes
Inference: Inference Code
FROM_REMOTE=True
base_model = 'llama2'
peft_model = 'FinGPT/fingpt-mt_llama2-7b_lora' if FROM_REMOTE else 'finetuned_models/MT-llama2-linear_202309210126'
model, tokenizer = load_model(base_model, peft_model, FROM_REMOTE)
demo_tasks = [
'Financial Sentiment Analysis',
'Financial Relation Extraction',
'Financial Headline Classification',
'Financial Named Entity Recognition',
]
demo_inputs = [
"Glaxo's ViiV Healthcare Signs China Manufacturing Deal With Desano",
"Apple Inc Chief Executive Steve Jobs sought to soothe investor concerns about his health on Monday, saying his weight loss was caused by a hormone imbalance that is relatively simple to treat.",
'gold trades in red in early trade; eyes near-term range at rs 28,300-28,600',
'This LOAN AND SECURITY AGREEMENT dated January 27 , 1999 , between SILICON VALLEY BANK (" Bank "), a California - chartered bank with its principal place of business at 3003 Tasman Drive , Santa Clara , California 95054 with a loan production office located at 40 William St ., Ste .',
]
demo_instructions = [
'What is the sentiment of this news? Please choose an answer from {negative/neutral/positive}.',
'Given phrases that describe the relationship between two words/phrases as options, extract the word/phrase pair and the corresponding lexical relationship between them from the input text. The output format should be "relation1: word1, word2; relation2: word3, word4". Options: product/material produced, manufacturer, distributed by, industry, position held, original broadcaster, owned by, founded by, distribution format, headquarters location, stock exchange, currency, parent organization, chief executive officer, director/manager, owner of, operator, member of, employer, chairperson, platform, subsidiary, legal form, publisher, developer, brand, business division, location of formation, creator.',
'Does the news headline talk about price going up? Please choose an answer from {Yes/No}.',
'Please extract entities and their types from the input sentence, entity types should be chosen from {person/organization/location}.',
]
test_demo(model, tokenizer)
Inference Results:
==== Financial Sentiment Analysis ====
Instruction: What is the sentiment of this news? Please choose an answer from {negative/neutral/positive}.
Input: Glaxo's ViiV Healthcare Signs China Manufacturing Deal With Desano
Answer: positive
==== Financial Relation Extraction ====
Instruction: Given phrases that describe the relationship between two words/phrases as options, extract the word/phrase pair and the corresponding lexical relationship between them from the input text. The output format should be "relation1: word1, word2; relation2: word3, word4". Options: product/material produced, manufacturer, distributed by, industry, position held, original broadcaster, owned by, founded by, distribution format, headquarters location, stock exchange, currency, parent organization, chief executive officer, director/manager, owner of, operator, member of, employer, chairperson, platform, subsidiary, legal form, publisher, developer, brand, business division, location of formation, creator.
Input: Apple Inc Chief Executive Steve Jobs sought to soothe investor concerns about his health on Monday, saying his weight loss was caused by a hormone imbalance that is relatively simple to treat.
Answer: employer: Steve Jobs, Apple Inc
==== Financial Headline Classification ====
Instruction: Does the news headline talk about price going up? Please choose an answer from {Yes/No}.
Input: gold trades in red in early trade; eyes near-term range at rs 28,300-28,600
Answer: No
==== Financial Named Entity Recognition ====
Instruction: Please extract entities and their types from the input sentence, entity types should be chosen from {person/organization/location}.
Input: This LOAN AND SECURITY AGREEMENT dated January 27, 1999, between SILICON VALLEY BANK (" Bank "), a California - chartered bank with its principal place of business at 3003 Tasman Drive, Santa Clara, California 95054 with a loan production office located at 40 William St., Ste.
Answer: SILICON VALLEY BANK is an organization, Bank is an organization, California is a location, bank is an organization, 3003 Tasman Drive is a location, Santa Clara is a location, California is a location, 40 William St is a location.
- PEFT 0.5.0