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flan-t5-bleu-squad-qg-120b
devagonal/flan-t5-bleu-squad-qg-120b
flan-t5-bleu-squad-qg-120b is a machine learning model from devagonal. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Feb 2, 2025
- Updated
- Feb 2, 2025
- SHA
- d929c435
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-bleu-squad-qg-120b
This model is a fine-tuned version of google/flan-t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 19.0104
- Bleu: 0.0272
- Precisions: [0.32, 0.15428571428571428, 0.04666666666666667, 0.016]
- Brevity Penalty: 0.3491
- Length Ratio: 0.4872
- Translation Length: 400
- Reference Length: 821
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: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length |
|---|---|---|---|---|---|---|---|---|---|
| 28.5845 | 1.0 | 5 | 32.7207 | 0.0224 | [0.3176470588235294, 0.18620689655172415, 0.058333333333333334, 0.021052631578947368] | 0.2430 | 0.4141 | 340 | 821 |
| 24.0236 | 2.0 | 10 | 26.1977 | 0.0252 | [0.29210526315789476, 0.16363636363636364, 0.05, 0.017391304347826087] | 0.3133 | 0.4629 | 380 | 821 |
| 19.6925 | 3.0 | 15 | 22.4190 | 0.0268 | [0.3, 0.15428571428571428, 0.04666666666666667, 0.016] | 0.3491 | 0.4872 | 400 | 821 |
| 18.2172 | 4.0 | 20 | 19.9877 | 0.0272 | [0.32, 0.15428571428571428, 0.04666666666666667, 0.016] | 0.3491 | 0.4872 | 400 | 821 |
| 17.5741 | 5.0 | 25 | 19.0104 | 0.0272 | [0.32, 0.15428571428571428, 0.04666666666666667, 0.016] | 0.3491 | 0.4872 | 400 | 821 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Feb 2, 2025
- Updated
- Feb 2, 2025