Instructions to use Gayathri142214002/Question_Generation_ComQ_7_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gayathri142214002/Question_Generation_ComQ_7_2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Gayathri142214002/Question_Generation_ComQ_7_2") model = AutoModelForSeq2SeqLM.from_pretrained("Gayathri142214002/Question_Generation_ComQ_7_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Question_Generation_ComQ_7_2
This model is a fine-tuned version of Gayathri142214002/Question_Generation_ComQ_6 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3358
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 |
|---|---|---|---|
| 0.2389 | 0.23 | 100 | 0.2383 |
| 0.2843 | 0.47 | 200 | 0.2704 |
| 0.2913 | 0.7 | 300 | 0.2648 |
| 0.2755 | 0.94 | 400 | 0.2607 |
| 0.2329 | 1.17 | 500 | 0.2916 |
| 0.2302 | 1.41 | 600 | 0.2971 |
| 0.2426 | 1.64 | 700 | 0.2861 |
| 0.2546 | 1.88 | 800 | 0.2906 |
| 0.2163 | 2.11 | 900 | 0.2995 |
| 0.211 | 2.35 | 1000 | 0.3133 |
| 0.2202 | 2.58 | 1100 | 0.3082 |
| 0.2352 | 2.82 | 1200 | 0.3039 |
| 0.2169 | 3.05 | 1300 | 0.2971 |
| 0.1932 | 3.29 | 1400 | 0.3126 |
| 0.2043 | 3.52 | 1500 | 0.3173 |
| 0.2066 | 3.76 | 1600 | 0.3100 |
| 0.2099 | 3.99 | 1700 | 0.3101 |
| 0.1672 | 4.23 | 1800 | 0.3226 |
| 0.1813 | 4.46 | 1900 | 0.3295 |
| 0.1823 | 4.7 | 2000 | 0.3280 |
| 0.1967 | 4.93 | 2100 | 0.3247 |
| 0.1725 | 5.17 | 2200 | 0.3330 |
| 0.1723 | 5.4 | 2300 | 0.3336 |
| 0.162 | 5.64 | 2400 | 0.3360 |
| 0.1716 | 5.87 | 2500 | 0.3337 |
| 0.1659 | 6.11 | 2600 | 0.3340 |
| 0.1553 | 6.34 | 2700 | 0.3355 |
| 0.1537 | 6.58 | 2800 | 0.3366 |
| 0.1589 | 6.81 | 2900 | 0.3358 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Downloads last month
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Base model
Gayathri142214002/Question_Generation_ComQ_6