Transformers
PyTorch
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use Gayathri142214002/Question_Generation_ComQ_8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gayathri142214002/Question_Generation_ComQ_8 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Gayathri142214002/Question_Generation_ComQ_8") model = AutoModelForSeq2SeqLM.from_pretrained("Gayathri142214002/Question_Generation_ComQ_8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Question_Generation_ComQ_8
This model is a fine-tuned version of Gayathri142214002/Question_Generation_ComQ_7 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2468
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
|---|---|---|---|
| 0.2272 | 0.88 | 100 | 0.2013 |
| 0.2032 | 1.76 | 200 | 0.2146 |
| 0.1838 | 2.64 | 300 | 0.2305 |
| 0.1816 | 3.52 | 400 | 0.2394 |
| 0.1737 | 4.4 | 500 | 0.2414 |
| 0.1674 | 5.27 | 600 | 0.2454 |
| 0.1611 | 6.15 | 700 | 0.2468 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
- Downloads last month
- 10
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support