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ACoRN_Flan-t5-large-triviaQA
Alan96/ACoRN_Flan-t5-large-triviaQA
ACoRN_Flan-t5-large-triviaQA is a machine learning model from Alan96. 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
- Apr 29, 2025
- Updated
- Apr 29, 2025
- SHA
- ce1d956c
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-large-train_r_aug-tqa
This model is a fine-tuned version of google/flan-t5-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6242
- Model Preparation Time: 0.0137
- Gen Len: 45.6732
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: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- total_eval_batch_size: 16
- 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: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Gen Len |
|---|---|---|---|---|---|
| 0.8038 | 0.1659 | 1000 | 0.6971 | 0.0137 | 44.2541 |
| 0.8712 | 0.3319 | 2000 | 0.6793 | 0.0137 | 47.4154 |
| 0.7521 | 0.4978 | 3000 | 0.6684 | 0.0137 | 41.3979 |
| 0.6859 | 0.6638 | 4000 | 0.6545 | 0.0137 | 45.1304 |
| 0.7234 | 0.8297 | 5000 | 0.6476 | 0.0137 | 45.7875 |
| 0.7439 | 0.9957 | 6000 | 0.6396 | 0.0137 | 40.4657 |
| 0.6351 | 1.1616 | 7000 | 0.6441 | 0.0137 | 42.3456 |
| 0.6851 | 1.3276 | 8000 | 0.6383 | 0.0137 | 43.8663 |
| 0.6932 | 1.4935 | 9000 | 0.6330 | 0.0137 | 45.9931 |
| 0.6506 | 1.6595 | 10000 | 0.6318 | 0.0137 | 42.6188 |
| 0.6577 | 1.8254 | 11000 | 0.6277 | 0.0137 | 45.5687 |
| 0.6659 | 1.9914 | 12000 | 0.6242 | 0.0137 | 45.6732 |
| 0.5711 | 2.1573 | 13000 | 0.6308 | 0.0137 | 45.9669 |
| 0.5918 | 2.3233 | 14000 | 0.6282 | 0.0137 | 44.9547 |
| 0.6076 | 2.4892 | 15000 | 0.6291 | 0.0137 | 43.6648 |
| 0.5828 | 2.6552 | 16000 | 0.6272 | 0.0137 | 43.8111 |
| 0.6006 | 2.8211 | 17000 | 0.6256 | 0.0137 | 44.7149 |
| 0.554 | 2.9871 | 18000 | 0.6251 | 0.0137 | 44.5414 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.21.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Apr 29, 2025
- Updated
- Apr 29, 2025