Instructions to use Gayathri142214002/Question_Generation_ComQ_8_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gayathri142214002/Question_Generation_ComQ_8_2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Gayathri142214002/Question_Generation_ComQ_8_2") model = AutoModelForSeq2SeqLM.from_pretrained("Gayathri142214002/Question_Generation_ComQ_8_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Question_Generation_ComQ_8_2
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: 0.3219
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 |
|---|---|---|---|
| 0.0484 | 0.22 | 100 | 0.3026 |
| 0.0462 | 0.44 | 200 | 0.3217 |
| 0.2787 | 0.66 | 300 | 0.2620 |
| 0.2864 | 0.88 | 400 | 0.2611 |
| 0.2528 | 1.1 | 500 | 0.2699 |
| 0.2224 | 1.32 | 600 | 0.2878 |
| 0.2303 | 1.54 | 700 | 0.2812 |
| 0.2525 | 1.76 | 800 | 0.2783 |
| 0.2429 | 1.98 | 900 | 0.2685 |
| 0.2147 | 2.2 | 1000 | 0.2849 |
| 0.202 | 2.42 | 1100 | 0.2939 |
| 0.2217 | 2.64 | 1200 | 0.2913 |
| 0.2213 | 2.86 | 1300 | 0.2834 |
| 0.1942 | 3.08 | 1400 | 0.2952 |
| 0.1866 | 3.3 | 1500 | 0.3072 |
| 0.1977 | 3.52 | 1600 | 0.3098 |
| 0.199 | 3.74 | 1700 | 0.3053 |
| 0.1964 | 3.96 | 1800 | 0.3017 |
| 0.1672 | 4.18 | 1900 | 0.3125 |
| 0.1669 | 4.4 | 2000 | 0.3182 |
| 0.1904 | 4.62 | 2100 | 0.3193 |
| 0.1744 | 4.84 | 2200 | 0.3132 |
| 0.177 | 5.06 | 2300 | 0.3130 |
| 0.1583 | 5.28 | 2400 | 0.3172 |
| 0.1676 | 5.5 | 2500 | 0.3168 |
| 0.1662 | 5.72 | 2600 | 0.3185 |
| 0.1703 | 5.94 | 2700 | 0.3164 |
| 0.1553 | 6.16 | 2800 | 0.3193 |
| 0.1557 | 6.38 | 2900 | 0.3201 |
| 0.1465 | 6.6 | 3000 | 0.3208 |
| 0.1549 | 6.82 | 3100 | 0.3219 |
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_7