metadata
tags:
- generated_from_trainer
- twitter-financial-topic-classification
- financial
- stocks
- twitter
datasets:
- zeroshot/twitter-financial-news-topic
metrics:
- accuracy
- f1
- precision
- recall
widget:
- text: >-
Here are Thursday's biggest analyst calls: Apple, Amazon, Tesla, Palantir,
DocuSign, Exxon & more
example_title: Analyst Update'
- text: >-
LIVE: ECB surprises with 50bps hike, ending its negative rate era.
President Christine Lagarde is taking questions
example_title: Fed | Central Banks
- text: >-
Goldman Sachs traders countered the industry’s underwriting slump with
revenue gains that raced past analysts’ estimates. The trading operation
posted a 32% surge in second-quarter revenue that included another banner
period for fixed income
example_title: Company | Product News
- text: >-
China Evergrande Group’s onshore bond holders rejected a plan by the
distressed developer to further extend a bond payment which was due on
Friday. Rebecca Choong Wilkins reports on Bloomberg Television
example_title: Treasuries | Corporate Debt
- text: >-
Investing Club: Morgan Stanley's dividend, buyback pay us for our patience
after quarterly missteps
example_title: Dividend
- text: >-
Investing Club: Our takes on Amazon and Apple heading into next week's
earnings reports
example_title: Earnings
- text: >-
JUST RELEASED: Oil Price Dynamics Report → Over the past week, oil prices
decreased as supply expectations rose and anticipated demand remained
unchanged.
example_title: Energy | Oil
- text: >-
Delta Air Lines fell short of profit expectations in the second quarter
and said high operating costs will persist through the rest of the year.
Bloomberg Opinion's Brooke Sutherland has more on 'Bloomberg Markets'
example_title: Financials
- text: >-
BREAKING: The Indian rupee plummets to a record 80 per US dollar as
foreign investors pull out money from the nation's stocks
example_title: Currencies
- text: >-
Twitter and Elon Musk are now in a high stakes/high risk situation, one
analyst said.
example_title: General News | Opinion
- text: >-
Copper prices are signaling that investors are bearish on the economy,
strategist says
example_title: Gold | Metals | Materials
- text: >-
Johnson & Johnson CFO Joe Wolk says the company is positioned for the long
term and the plans for its consumer operations include an IPO. He speaks
on 'Bloomberg Markets'
example_title: IPO
- text: >-
Company and Elon Musk are set for a blockbuster courtroom battle over
Musk’s attempt to terminate his $44 billion acquisition deal for $TWTR,
according to Wedbush analyst Dan Ives.
example_title: Legal | Regulation
- text: >-
Amazon to buy primary health care provider One Medical for roughly $3.9
billion
example_title: M&A | Investments
- text: >-
Barclays Senior Analyst For Equity Research Jason Goldberg: 'Price
expectations have changed.'' The global markets business recorded $6.47
billion of revenue in the quarter with rates, commodities and currencies
helping drive the fixed-income gains.
example_title: Macro
- text: >-
US stocks push higher in a volatile session. We break it down on The
Countdown to The Close
example_title: Markets
- text: Zelenskyy fires security chiefs over ‘treasonous’ officials
example_title: Politics
- text: Airbnb co-founder Joe Gebbia is stepping down
example_title: Personnel Change
- text: French power group EDF requests its shares be suspended
example_title: Stock Commentary
- text: >-
JUST IN: Alibaba shares slide as much as 5.7%, bringing this week's slump
to over 15%, after it reportedly faced a data-theft inquiry
example_title: Stock Movement
model-index:
- name: finbert-tone-finetuned-finance-topic-classification
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: twitter-financial-news-topic
type: finance
metrics:
- type: F1
name: F1
value: 0.910647
- type: accuracy
name: accuracy
value: 0.910615
finbert-tone-finetuned-finance-topic-classification
This model is a fine-tuned version of yiyanghkust/finbert-tone on Twitter Financial News Topic dataset. It achieves the following results on the evaluation set:
- Loss: 0.509021
- Accuracy: 0.910615
- F1: 0.910647
- Precision: 0.911335
- Recall: 0.910615
Model description
Model determines the financial topic of given tweets over 20 various topics. Given the unbalanced distribution of the class labels, the weights were adjusted to pay attention to the less sampled labels which should increase overall performance..
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 266 | 0.5152 | 0.8552 | 0.8504 | 0.8508 | 0.8552 |
| 0.7618 | 2.0 | 532 | 0.3999 | 0.8790 | 0.8781 | 0.8842 | 0.8790 |
| 0.7618 | 3.0 | 798 | 0.3628 | 0.8943 | 0.8940 | 0.8958 | 0.8943 |
| 0.16 | 4.0 | 1064 | 0.3776 | 0.8997 | 0.9001 | 0.9025 | 0.8997 |
| 0.16 | 5.0 | 1330 | 0.4286 | 0.8999 | 0.9002 | 0.9022 | 0.8999 |
| 0.058 | 6.0 | 1596 | 0.4500 | 0.9043 | 0.9042 | 0.9055 | 0.9043 |
| 0.058 | 7.0 | 1862 | 0.4689 | 0.9021 | 0.9017 | 0.9026 | 0.9021 |
| 0.0267 | 8.0 | 2128 | 0.4918 | 0.9031 | 0.9029 | 0.9039 | 0.9031 |
| 0.0267 | 9.0 | 2394 | 0.5030 | 0.9048 | 0.9049 | 0.9060 | 0.9048 |
| 0.0177 | 10.0 | 2660 | 0.5052 | 0.9033 | 0.9034 | 0.9044 | 0.9033 |
| 0.0177 | 11.0 | 2926 | 0.5265 | 0.9036 | 0.9034 | 0.9055 | 0.9036 |
| 0.013 | 12.0 | 3192 | 0.5267 | 0.9041 | 0.9041 | 0.9058 | 0.9041 |
| 0.013 | 13.0 | 3458 | 0.5090 | 0.9106 | 0.9106 | 0.9113 | 0.9106 |
| 0.0105 | 14.0 | 3724 | 0.5315 | 0.9067 | 0.9067 | 0.9080 | 0.9067 |
| 0.0105 | 15.0 | 3990 | 0.5339 | 0.9084 | 0.9084 | 0.9093 | 0.9084 |
| 0.0068 | 16.0 | 4256 | 0.5414 | 0.9072 | 0.9074 | 0.9088 | 0.9072 |
| 0.0051 | 17.0 | 4522 | 0.5460 | 0.9092 | 0.9091 | 0.9102 | 0.9092 |
| 0.0051 | 18.0 | 4788 | 0.5438 | 0.9072 | 0.9073 | 0.9081 | 0.9072 |
| 0.0035 | 19.0 | 5054 | 0.5474 | 0.9072 | 0.9073 | 0.9080 | 0.9072 |
| 0.0035 | 20.0 | 5320 | 0.5484 | 0.9079 | 0.9080 | 0.9087 | 0.9079 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2