flan-t5-base-squad-qag
This model is a fine-tuned version of google/flan-t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 15.5366
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 46.6459 | 0.5714 | 1 | 43.1485 |
| 65.3532 | 1.5714 | 2 | 41.6135 |
| 62.735 | 2.5714 | 3 | 40.4950 |
| 61.766 | 3.5714 | 4 | 39.5923 |
| 57.7849 | 4.5714 | 5 | 38.7835 |
| 55.8212 | 5.5714 | 6 | 38.0234 |
| 55.277 | 6.5714 | 7 | 37.3084 |
| 53.3929 | 7.5714 | 8 | 36.6244 |
| 53.3042 | 8.5714 | 9 | 35.9682 |
| 51.6622 | 9.5714 | 10 | 35.3432 |
| 50.679 | 10.5714 | 11 | 34.7521 |
| 49.5895 | 11.5714 | 12 | 34.1904 |
| 48.219 | 12.5714 | 13 | 33.6558 |
| 47.7489 | 13.5714 | 14 | 33.1496 |
| 46.8016 | 14.5714 | 15 | 32.6729 |
| 45.2487 | 15.5714 | 16 | 32.2232 |
| 45.3148 | 16.5714 | 17 | 31.7991 |
| 44.3454 | 17.5714 | 18 | 31.3964 |
| 43.6766 | 18.5714 | 19 | 31.0145 |
| 42.8757 | 19.5714 | 20 | 30.6499 |
| 42.9431 | 20.5714 | 21 | 30.2991 |
| 41.7531 | 21.5714 | 22 | 29.9607 |
| 41.2977 | 22.5714 | 23 | 29.6343 |
| 40.7757 | 23.5714 | 24 | 29.3154 |
| 40.0453 | 24.5714 | 25 | 29.0031 |
| 39.602 | 25.5714 | 26 | 28.6966 |
| 39.7306 | 26.5714 | 27 | 28.3944 |
| 38.703 | 27.5714 | 28 | 28.0947 |
| 38.7594 | 28.5714 | 29 | 27.7978 |
| 38.3422 | 29.5714 | 30 | 27.5051 |
| 38.1699 | 30.5714 | 31 | 27.2152 |
| 37.9031 | 31.5714 | 32 | 26.9286 |
| 36.9734 | 32.5714 | 33 | 26.6434 |
| 37.0667 | 33.5714 | 34 | 26.3599 |
| 36.466 | 34.5714 | 35 | 26.0803 |
| 35.9406 | 35.5714 | 36 | 25.8051 |
| 35.6333 | 36.5714 | 37 | 25.5321 |
| 35.3167 | 37.5714 | 38 | 25.2619 |
| 35.3965 | 38.5714 | 39 | 24.9950 |
| 34.5731 | 39.5714 | 40 | 24.7318 |
| 34.2446 | 40.5714 | 41 | 24.4734 |
| 34.2668 | 41.5714 | 42 | 24.2188 |
| 33.6151 | 42.5714 | 43 | 23.9683 |
| 33.5523 | 43.5714 | 44 | 23.7208 |
| 33.0644 | 44.5714 | 45 | 23.4754 |
| 32.7476 | 45.5714 | 46 | 23.2334 |
| 32.9809 | 46.5714 | 47 | 22.9938 |
| 32.0039 | 47.5714 | 48 | 22.7560 |
| 32.0855 | 48.5714 | 49 | 22.5215 |
| 31.6121 | 49.5714 | 50 | 22.2902 |
| 31.5072 | 50.5714 | 51 | 22.0626 |
| 31.0177 | 51.5714 | 52 | 21.8383 |
| 30.7915 | 52.5714 | 53 | 21.6181 |
| 30.6385 | 53.5714 | 54 | 21.4022 |
| 30.0557 | 54.5714 | 55 | 21.1892 |
| 30.2011 | 55.5714 | 56 | 20.9796 |
| 29.8038 | 56.5714 | 57 | 20.7722 |
| 29.5406 | 57.5714 | 58 | 20.5675 |
| 29.2149 | 58.5714 | 59 | 20.3655 |
| 29.2198 | 59.5714 | 60 | 20.1660 |
| 28.8561 | 60.5714 | 61 | 19.9673 |
| 28.6416 | 61.5714 | 62 | 19.7716 |
| 28.8112 | 62.5714 | 63 | 19.5786 |
| 28.2165 | 63.5714 | 64 | 19.3885 |
| 27.8991 | 64.5714 | 65 | 19.2027 |
| 27.5846 | 65.5714 | 66 | 19.0196 |
| 27.2384 | 66.5714 | 67 | 18.8399 |
| 27.0191 | 67.5714 | 68 | 18.6630 |
| 27.1786 | 68.5714 | 69 | 18.4899 |
| 26.8166 | 69.5714 | 70 | 18.3193 |
| 26.5479 | 70.5714 | 71 | 18.1547 |
| 26.083 | 71.5714 | 72 | 17.9942 |
| 26.2608 | 72.5714 | 73 | 17.8381 |
| 26.4425 | 73.5714 | 74 | 17.6867 |
| 25.715 | 74.5714 | 75 | 17.5401 |
| 25.3579 | 75.5714 | 76 | 17.3974 |
| 25.4759 | 76.5714 | 77 | 17.2583 |
| 25.494 | 77.5714 | 78 | 17.1240 |
| 25.2856 | 78.5714 | 79 | 16.9947 |
| 24.9815 | 79.5714 | 80 | 16.8690 |
| 25.0225 | 80.5714 | 81 | 16.7476 |
| 24.868 | 81.5714 | 82 | 16.6309 |
| 24.7249 | 82.5714 | 83 | 16.5196 |
| 24.446 | 83.5714 | 84 | 16.4145 |
| 24.7399 | 84.5714 | 85 | 16.3154 |
| 24.1898 | 85.5714 | 86 | 16.2216 |
| 24.451 | 86.5714 | 87 | 16.1322 |
| 24.1094 | 87.5714 | 88 | 16.0485 |
| 23.9994 | 88.5714 | 89 | 15.9708 |
| 23.7422 | 89.5714 | 90 | 15.8995 |
| 23.967 | 90.5714 | 91 | 15.8342 |
| 23.7289 | 91.5714 | 92 | 15.7749 |
| 23.5241 | 92.5714 | 93 | 15.7217 |
| 23.5077 | 93.5714 | 94 | 15.6754 |
| 23.7215 | 94.5714 | 95 | 15.6356 |
| 23.5504 | 95.5714 | 96 | 15.6024 |
| 23.4054 | 96.5714 | 97 | 15.5761 |
| 23.4654 | 97.5714 | 98 | 15.5563 |
| 23.3449 | 98.5714 | 99 | 15.5431 |
| 23.5244 | 99.5714 | 100 | 15.5366 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0