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flan-t5-base-trading_candles
Isotonic/flan-t5-base-trading_candles
flan-t5-base-trading_candles is a text generation model from Isotonic. Use it when you need the model to write or continue text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Generation
- Library
- transformers
- Model type
- t5
- Access
- Public
- Created
- Aug 22, 2023
- Updated
- Aug 25, 2023
- SHA
- f27d0ebe
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Base models
Model card
From the Hugging Face model README
<!-- 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 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
- Task
- Text Generation
- Library
- transformers
- Type
- t5
- Created
- Aug 22, 2023
- Updated
- Aug 25, 2023