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---
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
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# flan-t5-base-trading_candles
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on [0xMaka/trading-candles-subset-qa-format](https://huggingface.co/datasets/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 |