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Question_Generation_ComQ_onT5base_withDataGen7
Gayathri142214002/Question_Generation_ComQ_onT5base_withDataGen7
Question_Generation_ComQ_onT5base_withDataGen7 is a machine learning model from Gayathri142214002. 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
- Jan 26, 2024
- Updated
- Jan 26, 2024
- SHA
- 770c5f9b
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. -->
Question_Generation_ComQ_onT5base_withDataGen7
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3923
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7546 | 0.23 | 1000 | 0.5504 |
| 0.6013 | 0.47 | 2000 | 0.5134 |
| 0.557 | 0.7 | 3000 | 0.4834 |
| 0.5217 | 0.94 | 4000 | 0.4513 |
| 0.449 | 1.17 | 5000 | 0.4519 |
| 0.4441 | 1.41 | 6000 | 0.4389 |
| 0.439 | 1.64 | 7000 | 0.4322 |
| 0.4355 | 1.88 | 8000 | 0.4153 |
| 0.3996 | 2.11 | 9000 | 0.4263 |
| 0.388 | 2.35 | 10000 | 0.4183 |
| 0.3856 | 2.58 | 11000 | 0.4129 |
| 0.3782 | 2.82 | 12000 | 0.4101 |
| 0.3719 | 3.05 | 13000 | 0.4091 |
| 0.3395 | 3.29 | 14000 | 0.4091 |
| 0.3453 | 3.52 | 15000 | 0.4053 |
| 0.3538 | 3.76 | 16000 | 0.3933 |
| 0.3468 | 3.99 | 17000 | 0.3897 |
| 0.3128 | 4.22 | 18000 | 0.4035 |
| 0.3191 | 4.46 | 19000 | 0.4005 |
| 0.322 | 4.69 | 20000 | 0.3944 |
| 0.3204 | 4.93 | 21000 | 0.3881 |
| 0.302 | 5.16 | 22000 | 0.3951 |
| 0.2947 | 5.4 | 23000 | 0.3948 |
| 0.3011 | 5.63 | 24000 | 0.3932 |
| 0.303 | 5.87 | 25000 | 0.3873 |
| 0.2902 | 6.1 | 26000 | 0.3916 |
| 0.2777 | 6.34 | 27000 | 0.3940 |
| 0.2811 | 6.57 | 28000 | 0.3937 |
| 0.2815 | 6.81 | 29000 | 0.3923 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Jan 26, 2024
- Updated
- Jan 26, 2024