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Question_Generation_ComQ_4
This model is a fine-tuned version of Gayathri142214002/Question_Generation_ComQ_3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4193
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 |
|---|---|---|---|
| 0.3616 | 0.16 | 50 | 0.3498 |
| 0.3949 | 0.32 | 100 | 0.3389 |
| 0.3926 | 0.48 | 150 | 0.3321 |
| 0.3946 | 0.64 | 200 | 0.3386 |
| 0.414 | 0.8 | 250 | 0.3315 |
| 0.3789 | 0.96 | 300 | 0.3299 |
| 0.2962 | 1.12 | 350 | 0.3469 |
| 0.3104 | 1.28 | 400 | 0.3606 |
| 0.2821 | 1.44 | 450 | 0.3593 |
| 0.3011 | 1.59 | 500 | 0.3552 |
| 0.3273 | 1.75 | 550 | 0.3500 |
| 0.3247 | 1.91 | 600 | 0.3456 |
| 0.2903 | 2.07 | 650 | 0.3635 |
| 0.2373 | 2.23 | 700 | 0.3813 |
| 0.2472 | 2.39 | 750 | 0.3901 |
| 0.25 | 2.55 | 800 | 0.3773 |
| 0.2808 | 2.71 | 850 | 0.3766 |
| 0.2564 | 2.87 | 900 | 0.3698 |
| 0.268 | 3.03 | 950 | 0.3717 |
| 0.2194 | 3.19 | 1000 | 0.3876 |
| 0.2091 | 3.35 | 1050 | 0.3980 |
| 0.235 | 3.51 | 1100 | 0.3975 |
| 0.2292 | 3.67 | 1150 | 0.4061 |
| 0.2486 | 3.83 | 1200 | 0.3973 |
| 0.2601 | 3.99 | 1250 | 0.3901 |
| 0.1845 | 4.15 | 1300 | 0.3959 |
| 0.2079 | 4.31 | 1350 | 0.3996 |
| 0.1817 | 4.47 | 1400 | 0.4128 |
| 0.2083 | 4.63 | 1450 | 0.4175 |
| 0.2511 | 4.78 | 1500 | 0.4100 |
| 0.2151 | 4.94 | 1550 | 0.4054 |
| 0.2039 | 5.1 | 1600 | 0.4078 |
| 0.1864 | 5.26 | 1650 | 0.4082 |
| 0.1894 | 5.42 | 1700 | 0.4147 |
| 0.1988 | 5.58 | 1750 | 0.4154 |
| 0.1921 | 5.74 | 1800 | 0.4151 |
| 0.1948 | 5.9 | 1850 | 0.4124 |
| 0.1813 | 6.06 | 1900 | 0.4108 |
| 0.1695 | 6.22 | 1950 | 0.4153 |
| 0.1691 | 6.38 | 2000 | 0.4179 |
| 0.1628 | 6.54 | 2050 | 0.4188 |
| 0.1724 | 6.7 | 2100 | 0.4188 |
| 0.1708 | 6.86 | 2150 | 0.4193 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
