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Based Bert for sequence classification

This model is a POC and shouldn't be used for any production task.

Model description

Based Bert SC is a text classification bot for binary classification of a trading candles opening and closing prices.

Uses and limitations

This model can reliably return the bullish or bearish status of a candle given the opening, closing, high and low, in a format shown. It will have trouble if the order of the numbers change (even if tags are included).

How to use

You can use this model directly with a pipeline

>>> from transformers import pipeline
>>> pipe = pipeline("text-classification", model="0xMaka/based-bert-sc")
>>> text = "identify candle: open: 21788.19, close: 21900, high: 21965.23, low: 21788.19"
>>> pipe(text)
[{'label': 'Bullish', 'score': 0.9999682903289795}]

Finetuning

For parameters: https://github.com/0xMaka/based-bert-sc/blob/main/trainer.py

This model was fine tuned on an RTX-3060-Mobile

// BUS_WIDTH = 192
// CLOCK_RATE = 1750 
// DDR_MULTI = 8 // DDR6
// BWTheoretical = (((CLOCK_RATE * (10 ** 6)) * (BUS_WIDTH/8)) * DDR_MULI) / (10 ** 9) 
// BWTheoretical == 336 GB/s

Self-measured effective (GB/s): 316.280736

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Model size
67M params
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F32
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Dataset used to train 0xMaka/based-bert-sc