flan-t5-base-squad-qag-b
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: 4.3126
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: 2e-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 | 41.6529 |
| 62.2881 | 1.5714 | 2 | 39.6635 |
| 57.9979 | 2.5714 | 3 | 38.0827 |
| 55.2983 | 3.5714 | 4 | 36.6795 |
| 52.2218 | 4.5714 | 5 | 35.3840 |
| 49.5878 | 5.5714 | 6 | 34.1714 |
| 48.3754 | 6.5714 | 7 | 33.0814 |
| 46.4029 | 7.5714 | 8 | 32.1042 |
| 45.7095 | 8.5714 | 9 | 31.2362 |
| 43.622 | 9.5714 | 10 | 30.4637 |
| 42.5298 | 10.5714 | 11 | 29.7723 |
| 41.374 | 11.5714 | 12 | 29.1297 |
| 40.0091 | 12.5714 | 13 | 28.5180 |
| 38.9493 | 13.5714 | 14 | 27.9190 |
| 38.4019 | 14.5714 | 15 | 27.3293 |
| 37.0155 | 15.5714 | 16 | 26.7453 |
| 36.6909 | 16.5714 | 17 | 26.1653 |
| 35.8302 | 17.5714 | 18 | 25.5881 |
| 35.0254 | 18.5714 | 19 | 25.0157 |
| 34.5181 | 19.5714 | 20 | 24.4471 |
| 33.9099 | 20.5714 | 21 | 23.8822 |
| 32.9181 | 21.5714 | 22 | 23.3236 |
| 32.3386 | 22.5714 | 23 | 22.7745 |
| 31.7004 | 23.5714 | 24 | 22.2330 |
| 30.7786 | 24.5714 | 25 | 21.6956 |
| 30.1637 | 25.5714 | 26 | 21.1577 |
| 29.9204 | 26.5714 | 27 | 20.6225 |
| 28.9905 | 27.5714 | 28 | 20.0852 |
| 28.6735 | 28.5714 | 29 | 19.5506 |
| 27.9501 | 29.5714 | 30 | 19.0144 |
| 27.358 | 30.5714 | 31 | 18.4755 |
| 26.9717 | 31.5714 | 32 | 17.9333 |
| 25.7062 | 32.5714 | 33 | 17.3834 |
| 25.5156 | 33.5714 | 34 | 16.8244 |
| 24.5697 | 34.5714 | 35 | 16.2665 |
| 23.9692 | 35.5714 | 36 | 15.6957 |
| 23.2353 | 36.5714 | 37 | 15.1122 |
| 22.5299 | 37.5714 | 38 | 14.5180 |
| 22.0458 | 38.5714 | 39 | 13.9129 |
| 20.8835 | 39.5714 | 40 | 13.2977 |
| 20.2673 | 40.5714 | 41 | 12.6807 |
| 19.8669 | 41.5714 | 42 | 12.0450 |
| 18.836 | 42.5714 | 43 | 11.3926 |
| 18.1732 | 43.5714 | 44 | 10.7243 |
| 17.1998 | 44.5714 | 45 | 10.0452 |
| 16.2139 | 45.5714 | 46 | 9.3454 |
| 16.225 | 46.5714 | 47 | 8.6436 |
| 14.549 | 47.5714 | 48 | 7.9531 |
| 14.4398 | 48.5714 | 49 | 7.2808 |
| 13.7322 | 49.5714 | 50 | 6.6608 |
| 12.4941 | 50.5714 | 51 | 6.1236 |
| 11.982 | 51.5714 | 52 | 5.7015 |
| 11.3853 | 52.5714 | 53 | 5.3868 |
| 10.7295 | 53.5714 | 54 | 5.1683 |
| 10.1794 | 54.5714 | 55 | 5.0195 |
| 9.8638 | 55.5714 | 56 | 4.9177 |
| 9.2193 | 56.5714 | 57 | 4.8455 |
| 9.1266 | 57.5714 | 58 | 4.7924 |
| 8.9316 | 58.5714 | 59 | 4.7506 |
| 8.3913 | 59.5714 | 60 | 4.7168 |
| 8.3446 | 60.5714 | 61 | 4.6880 |
| 8.0074 | 61.5714 | 62 | 4.6617 |
| 7.8951 | 62.5714 | 63 | 4.6376 |
| 7.7446 | 63.5714 | 64 | 4.6158 |
| 7.7313 | 64.5714 | 65 | 4.5963 |
| 7.5051 | 65.5714 | 66 | 4.5780 |
| 7.3933 | 66.5714 | 67 | 4.5608 |
| 7.3083 | 67.5714 | 68 | 4.5449 |
| 7.3168 | 68.5714 | 69 | 4.5301 |
| 7.1794 | 69.5714 | 70 | 4.5161 |
| 7.2062 | 70.5714 | 71 | 4.5032 |
| 7.1407 | 71.5714 | 72 | 4.4914 |
| 7.0435 | 72.5714 | 73 | 4.4803 |
| 7.0905 | 73.5714 | 74 | 4.4696 |
| 7.0244 | 74.5714 | 75 | 4.4592 |
| 6.9725 | 75.5714 | 76 | 4.4489 |
| 6.9754 | 76.5714 | 77 | 4.4392 |
| 6.9402 | 77.5714 | 78 | 4.4297 |
| 6.8599 | 78.5714 | 79 | 4.4207 |
| 6.8546 | 79.5714 | 80 | 4.4118 |
| 6.8619 | 80.5714 | 81 | 4.4032 |
| 6.7876 | 81.5714 | 82 | 4.3950 |
| 6.7963 | 82.5714 | 83 | 4.3869 |
| 6.8075 | 83.5714 | 84 | 4.3791 |
| 6.7802 | 84.5714 | 85 | 4.3718 |
| 6.7299 | 85.5714 | 86 | 4.3649 |
| 6.7649 | 86.5714 | 87 | 4.3583 |
| 6.7058 | 87.5714 | 88 | 4.3521 |
| 6.7104 | 88.5714 | 89 | 4.3464 |
| 6.6899 | 89.5714 | 90 | 4.3410 |
| 6.6947 | 90.5714 | 91 | 4.3360 |
| 6.6657 | 91.5714 | 92 | 4.3314 |
| 6.6323 | 92.5714 | 93 | 4.3273 |
| 6.6381 | 93.5714 | 94 | 4.3237 |
| 6.6417 | 94.5714 | 95 | 4.3206 |
| 6.6728 | 95.5714 | 96 | 4.3179 |
| 6.6866 | 96.5714 | 97 | 4.3158 |
| 6.634 | 97.5714 | 98 | 4.3142 |
| 6.6684 | 98.5714 | 99 | 4.3132 |
| 6.6304 | 99.5714 | 100 | 4.3126 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0