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t5_large-qg-aap
tiagoblima/t5_large-qg-aap
t5_large-qg-aap is a machine learning model from tiagoblima. 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 mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- t5
- Access
- Public
- Created
- Dec 29, 2023
- Updated
- Jan 3, 2024
- SHA
- 9b61df6f
Base models
Datasets
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. -->
t5_large-qg-aap
This model is a fine-tuned version of unicamp-dl/ptt5-large-t5-vocab on the tiagoblima/qg_squad_v1_pt dataset. It achieves the following results on the evaluation set:
- Loss: 5.5901
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: 0.005
- train_batch_size: 64
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.15 | 1.0 | 808 | 7.3361 |
| 5.3335 | 2.0 | 1616 | 6.4092 |
| 4.8807 | 3.0 | 2424 | 5.9132 |
| 4.6492 | 4.0 | 3232 | 5.6656 |
| 4.591 | 5.0 | 4040 | 5.5901 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0
- Library
- transformers
- Type
- t5
- License
- mit
- Created
- Dec 29, 2023
- Updated
- Jan 3, 2024