metadata
license: apache-2.0
base_model: albert/albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: startup-score
results: []
language:
- en
widget:
- text: >-
Company Name : Dropbox Inc. ,Gender: FEMALE, Company Description: Dropbox
lets you save and access all your files and photos in one place for easy
sharing. Easily share files & access team content from your computer,
mobile or any web browser, Company Website: https://www.dropbox.com/, Job
Titles: Chief Operating Officer (COO)/ Head of Operations, Business Model:
nan, Revenue: $50,001 - $250,000 (USD), Profit: Not generating profit yet
,Total External Funding: 4000000, Notable Investors: Y Combinator, Sequioa
Capital, Competition Region: North America, Team Size: Complementary team
with some founders having significant work experience Market Opportunity ,
Problem to be solved: Product solves a problem and has an attractive niche
in a large market. Very strong value proposition to customers. Clear
customer identification with unique positioning in mostly untapped market
(more than or equals to USD 1 billion)., Innovation: Some unique IP,
patents or data (pending patent) ,Business Model: Good revenue model /
business model is defined and has been validated with large number of
customers ,Scalability: Solution has no issues to scale globally or within
home country but scaling has not started ,Traction: Prototype testing with
initial customers (Beta testing)
startup-score
This model is a fine-tuned version of albert/albert-base-v2 on Startup Score Dataset. It achieves the following results on the evaluation set:
- Loss: 0.7827
- Accuracy: 0.25
- F1: 0.3000
- Precision: 0.375
- Recall: 0.25
- Accuracy Label Eligible: 0.0
- Accuracy Label Not eligible: 0.3333
Model description
More information needed
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1