Isotonic's picture
Update README.md
35b0374
metadata
base_model: google/flan-t5-base
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: flan-t5-base-trading_candles
    results: []
datasets:
  - 0xMaka/trading-candles-subset-qa-format
widget:
  - text: >-
      Context:
      -30811302.00,464.00,-156202.00,309984.00,276.00,7664.00,4174.00,824467.00,19741.12,19798.04,19860.18,19567.9 
      Question: identify candle
  - text: >-
      Context:
      867553.00,-4282049.00,6306.00,4440418.00,13.00,50962.00,101.00,59152496.00,39512.71,39477.49,39512.71,39380.74 
      Question: identify candle
  - text: >-
      Context:
      -206.00,626162.00,-35917428.00,-49739.00,6669939.00,64.00,19988.00,7094559.00,17752.71,17752.71,17752.71,17752.71 
      Question: find candle: Four Price Doji
pipeline_tag: text2text-generation

flan-t5-base-trading_candles

This model is a fine-tuned version of google/flan-t5-base on 0xMaka/trading-candles-subset-qa-format dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0061
  • Rouge1: 88.3665
  • Rouge2: 86.86
  • Rougel: 88.3651
  • Rougelsum: 88.3665
  • Gen Len: 18.9025

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: 3e-05
  • train_batch_size: 4
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
0.019 1.0 70009 0.0089 88.0774 86.4734 88.0734 88.0748 18.9022
0.0095 2.0 140018 0.0069 88.3636 86.8542 88.3612 88.3625 18.9016
0.0071 3.0 210027 0.0061 88.3665 86.86 88.3651 88.3665 18.9025

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3