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library_name: transformers
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-rouge-squad-qg-testc
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# flan-t5-rouge-squad-qg-testc
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3164
- Rouge1: 0.3601
- Rouge2: 0.1205
- Rougel: 0.3353
- Rougelsum: 0.3469
## 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: 80
- eval_batch_size: 80
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 320
- optimizer: Use 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: 160
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 62.2537 | 1.0 | 3 | 29.8253 | 0.0752 | 0.0204 | 0.0667 | 0.0672 |
| 51.2172 | 2.0 | 6 | 23.9235 | 0.0670 | 0.0190 | 0.0607 | 0.0609 |
| 42.2884 | 3.0 | 9 | 18.5434 | 0.0527 | 0.0175 | 0.0494 | 0.0496 |
| 33.4669 | 4.0 | 12 | 12.7318 | 0.0825 | 0.0407 | 0.0824 | 0.0827 |
| 25.4026 | 5.0 | 15 | 8.2492 | 0.0706 | 0.0377 | 0.0701 | 0.0704 |
| 20.0834 | 6.0 | 18 | 7.4425 | 0.0662 | 0.0349 | 0.0664 | 0.0666 |
| 16.9821 | 7.0 | 21 | 6.9817 | 0.0789 | 0.0347 | 0.0759 | 0.0776 |
| 14.7652 | 8.0 | 24 | 5.9311 | 0.0961 | 0.0435 | 0.0905 | 0.0937 |
| 12.7754 | 9.0 | 27 | 4.9313 | 0.1005 | 0.0444 | 0.0841 | 0.0916 |
| 11.6278 | 10.0 | 30 | 4.7801 | 0.1311 | 0.0577 | 0.1158 | 0.1214 |
| 10.6391 | 11.0 | 33 | 4.5698 | 0.0978 | 0.0372 | 0.0872 | 0.0905 |
| 9.9925 | 12.0 | 36 | 4.3618 | 0.1011 | 0.0440 | 0.0892 | 0.0934 |
| 9.4969 | 13.0 | 39 | 4.2002 | 0.1331 | 0.0582 | 0.1167 | 0.1221 |
| 9.0639 | 14.0 | 42 | 4.0571 | 0.1327 | 0.0564 | 0.1165 | 0.1217 |
| 8.7064 | 15.0 | 45 | 3.9041 | 0.1484 | 0.0628 | 0.1267 | 0.1337 |
| 8.3122 | 16.0 | 48 | 3.7252 | 0.1528 | 0.0543 | 0.1264 | 0.1345 |
| 8.0191 | 17.0 | 51 | 3.5352 | 0.1356 | 0.0502 | 0.1129 | 0.1204 |
| 7.7028 | 18.0 | 54 | 3.3741 | 0.1175 | 0.0426 | 0.0978 | 0.1045 |
| 7.3704 | 19.0 | 57 | 3.2478 | 0.1111 | 0.0460 | 0.0947 | 0.1004 |
| 7.059 | 20.0 | 60 | 3.1444 | 0.1052 | 0.0359 | 0.0842 | 0.0900 |
| 6.798 | 21.0 | 63 | 3.0483 | 0.1240 | 0.0444 | 0.0990 | 0.1057 |
| 6.6172 | 22.0 | 66 | 2.9450 | 0.1281 | 0.0416 | 0.1018 | 0.1100 |
| 6.397 | 23.0 | 69 | 2.8270 | 0.1294 | 0.0426 | 0.1058 | 0.1154 |
| 6.1434 | 24.0 | 72 | 2.6957 | 0.1192 | 0.0405 | 0.1011 | 0.1072 |
| 5.9183 | 25.0 | 75 | 2.5599 | 0.1207 | 0.0367 | 0.0974 | 0.1027 |
| 5.7236 | 26.0 | 78 | 2.4320 | 0.1124 | 0.0342 | 0.0950 | 0.1001 |
| 5.5052 | 27.0 | 81 | 2.3171 | 0.1121 | 0.0367 | 0.0961 | 0.1004 |
| 5.3234 | 28.0 | 84 | 2.2137 | 0.1322 | 0.0453 | 0.1132 | 0.1197 |
| 5.1292 | 29.0 | 87 | 2.1201 | 0.1464 | 0.0526 | 0.1248 | 0.1322 |
| 4.9497 | 30.0 | 90 | 2.0297 | 0.2406 | 0.0923 | 0.2102 | 0.2278 |
| 4.7775 | 31.0 | 93 | 1.9376 | 0.2581 | 0.0958 | 0.2229 | 0.2445 |
| 4.5872 | 32.0 | 96 | 1.8415 | 0.2783 | 0.0982 | 0.2442 | 0.2654 |
| 4.4228 | 33.0 | 99 | 1.7448 | 0.2993 | 0.1034 | 0.2699 | 0.2878 |
| 4.2818 | 34.0 | 102 | 1.6519 | 0.3106 | 0.1082 | 0.2810 | 0.2983 |
| 4.0818 | 35.0 | 105 | 1.5682 | 0.3280 | 0.1101 | 0.2963 | 0.3144 |
| 3.9575 | 36.0 | 108 | 1.4935 | 0.3307 | 0.1099 | 0.2992 | 0.3180 |
| 3.8176 | 37.0 | 111 | 1.4235 | 0.3464 | 0.1150 | 0.3140 | 0.3318 |
| 3.666 | 38.0 | 114 | 1.3551 | 0.3496 | 0.1166 | 0.3173 | 0.3349 |
| 3.5058 | 39.0 | 117 | 1.2865 | 0.3496 | 0.1166 | 0.3173 | 0.3349 |
| 3.3658 | 40.0 | 120 | 1.2200 | 0.3475 | 0.1166 | 0.3155 | 0.3334 |
| 3.2795 | 41.0 | 123 | 1.1562 | 0.3522 | 0.1179 | 0.3226 | 0.3386 |
| 3.1434 | 42.0 | 126 | 1.0954 | 0.3522 | 0.1179 | 0.3226 | 0.3386 |
| 3.0247 | 43.0 | 129 | 1.0422 | 0.3522 | 0.1179 | 0.3226 | 0.3386 |
| 2.9343 | 44.0 | 132 | 0.9925 | 0.3529 | 0.1185 | 0.3238 | 0.3393 |
| 2.8065 | 45.0 | 135 | 0.9465 | 0.3529 | 0.1185 | 0.3238 | 0.3393 |
| 2.7406 | 46.0 | 138 | 0.9023 | 0.3529 | 0.1185 | 0.3238 | 0.3393 |
| 2.6367 | 47.0 | 141 | 0.8608 | 0.3551 | 0.1166 | 0.3249 | 0.3427 |
| 2.4855 | 48.0 | 144 | 0.8197 | 0.3592 | 0.1172 | 0.3284 | 0.3457 |
| 2.4782 | 49.0 | 147 | 0.7803 | 0.3592 | 0.1172 | 0.3284 | 0.3457 |
| 2.3351 | 50.0 | 150 | 0.7463 | 0.3586 | 0.1149 | 0.3253 | 0.3446 |
| 2.2519 | 51.0 | 153 | 0.7154 | 0.3655 | 0.1169 | 0.3281 | 0.3517 |
| 2.1864 | 52.0 | 156 | 0.6861 | 0.3676 | 0.1171 | 0.3293 | 0.3530 |
| 2.128 | 53.0 | 159 | 0.6597 | 0.3676 | 0.1171 | 0.3293 | 0.3530 |
| 2.0668 | 54.0 | 162 | 0.6343 | 0.3676 | 0.1171 | 0.3293 | 0.3530 |
| 2.013 | 55.0 | 165 | 0.6098 | 0.3658 | 0.1167 | 0.3277 | 0.3506 |
| 1.9364 | 56.0 | 168 | 0.5872 | 0.3658 | 0.1167 | 0.3277 | 0.3506 |
| 1.8327 | 57.0 | 171 | 0.5655 | 0.3658 | 0.1167 | 0.3277 | 0.3506 |
| 1.7749 | 58.0 | 174 | 0.5456 | 0.3659 | 0.1169 | 0.3282 | 0.3506 |
| 1.7399 | 59.0 | 177 | 0.5276 | 0.3659 | 0.1169 | 0.3282 | 0.3506 |
| 1.7449 | 60.0 | 180 | 0.5110 | 0.3659 | 0.1169 | 0.3282 | 0.3506 |
| 1.6973 | 61.0 | 183 | 0.4959 | 0.3659 | 0.1169 | 0.3282 | 0.3506 |
| 1.5943 | 62.0 | 186 | 0.4822 | 0.3658 | 0.1185 | 0.3280 | 0.3506 |
| 1.5571 | 63.0 | 189 | 0.4703 | 0.3666 | 0.1194 | 0.3308 | 0.3519 |
| 1.5806 | 64.0 | 192 | 0.4589 | 0.3666 | 0.1194 | 0.3308 | 0.3519 |
| 1.5002 | 65.0 | 195 | 0.4471 | 0.3666 | 0.1194 | 0.3308 | 0.3519 |
| 1.4634 | 66.0 | 198 | 0.4356 | 0.3666 | 0.1194 | 0.3308 | 0.3519 |
| 1.4553 | 67.0 | 201 | 0.4250 | 0.3697 | 0.1216 | 0.3344 | 0.3559 |
| 1.4035 | 68.0 | 204 | 0.4164 | 0.3701 | 0.1222 | 0.3350 | 0.3561 |
| 1.4084 | 69.0 | 207 | 0.4090 | 0.3739 | 0.1255 | 0.3378 | 0.3594 |
| 1.3806 | 70.0 | 210 | 0.4023 | 0.3739 | 0.1255 | 0.3378 | 0.3594 |
| 1.3048 | 71.0 | 213 | 0.3957 | 0.3728 | 0.1254 | 0.3373 | 0.3576 |
| 1.2709 | 72.0 | 216 | 0.3891 | 0.3728 | 0.1254 | 0.3373 | 0.3576 |
| 1.2735 | 73.0 | 219 | 0.3828 | 0.3728 | 0.1254 | 0.3373 | 0.3576 |
| 1.2733 | 74.0 | 222 | 0.3768 | 0.3728 | 0.1254 | 0.3373 | 0.3576 |
| 1.2215 | 75.0 | 225 | 0.3715 | 0.3728 | 0.1254 | 0.3373 | 0.3576 |
| 1.2225 | 76.0 | 228 | 0.3669 | 0.3732 | 0.1255 | 0.3374 | 0.3580 |
| 1.1829 | 77.0 | 231 | 0.3628 | 0.3732 | 0.1255 | 0.3374 | 0.3580 |
| 1.162 | 78.0 | 234 | 0.3591 | 0.3722 | 0.1244 | 0.3362 | 0.3570 |
| 1.097 | 79.0 | 237 | 0.3556 | 0.3715 | 0.1236 | 0.3355 | 0.3564 |
| 1.1702 | 80.0 | 240 | 0.3519 | 0.3715 | 0.1236 | 0.3355 | 0.3564 |
| 1.1309 | 81.0 | 243 | 0.3483 | 0.3764 | 0.1259 | 0.3400 | 0.3608 |
| 1.0986 | 82.0 | 246 | 0.3451 | 0.3563 | 0.1178 | 0.3261 | 0.3428 |
| 1.1109 | 83.0 | 249 | 0.3422 | 0.3563 | 0.1178 | 0.3261 | 0.3428 |
| 1.0752 | 84.0 | 252 | 0.3397 | 0.3553 | 0.1167 | 0.3257 | 0.3417 |
| 1.0475 | 85.0 | 255 | 0.3374 | 0.3553 | 0.1167 | 0.3257 | 0.3417 |
| 1.0736 | 86.0 | 258 | 0.3353 | 0.3553 | 0.1167 | 0.3257 | 0.3417 |
| 1.0723 | 87.0 | 261 | 0.3333 | 0.3552 | 0.1176 | 0.3249 | 0.3409 |
| 1.0326 | 88.0 | 264 | 0.3314 | 0.3536 | 0.1165 | 0.3236 | 0.3394 |
| 1.0742 | 89.0 | 267 | 0.3297 | 0.3536 | 0.1165 | 0.3236 | 0.3394 |
| 1.0081 | 90.0 | 270 | 0.3281 | 0.3583 | 0.1172 | 0.3282 | 0.3447 |
| 1.0158 | 91.0 | 273 | 0.3266 | 0.3583 | 0.1172 | 0.3282 | 0.3447 |
| 1.032 | 92.0 | 276 | 0.3252 | 0.3632 | 0.1213 | 0.3330 | 0.3497 |
| 0.9778 | 93.0 | 279 | 0.3239 | 0.3632 | 0.1213 | 0.3330 | 0.3497 |
| 0.9834 | 94.0 | 282 | 0.3228 | 0.3624 | 0.1221 | 0.3323 | 0.3492 |
| 0.9913 | 95.0 | 285 | 0.3218 | 0.3624 | 0.1221 | 0.3323 | 0.3492 |
| 0.9963 | 96.0 | 288 | 0.3210 | 0.3624 | 0.1221 | 0.3323 | 0.3492 |
| 0.9759 | 97.0 | 291 | 0.3202 | 0.3605 | 0.1208 | 0.3344 | 0.3465 |
| 1.0011 | 98.0 | 294 | 0.3195 | 0.3605 | 0.1208 | 0.3344 | 0.3465 |
| 0.9895 | 99.0 | 297 | 0.3189 | 0.3605 | 0.1208 | 0.3344 | 0.3465 |
| 0.926 | 100.0 | 300 | 0.3183 | 0.3605 | 0.1208 | 0.3344 | 0.3465 |
| 0.9347 | 101.0 | 303 | 0.3178 | 0.3605 | 0.1208 | 0.3344 | 0.3465 |
| 1.0039 | 102.0 | 306 | 0.3173 | 0.3605 | 0.1208 | 0.3344 | 0.3465 |
| 0.9693 | 103.0 | 309 | 0.3170 | 0.3603 | 0.1205 | 0.3353 | 0.3469 |
| 0.9754 | 104.0 | 312 | 0.3167 | 0.3601 | 0.1205 | 0.3353 | 0.3469 |
| 0.9872 | 105.0 | 315 | 0.3165 | 0.3601 | 0.1205 | 0.3353 | 0.3469 |
| 1.0003 | 106.0 | 318 | 0.3164 | 0.3601 | 0.1205 | 0.3353 | 0.3469 |
| 1.9782 | 106.8 | 320 | 0.3164 | 0.3601 | 0.1205 | 0.3353 | 0.3469 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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