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---
library_name: peft
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my-lora-sum
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. -->
# my-lora-sum
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3452
- Rouge1: 2.9750
- Rouge2: 0.0640
- Rougel: 2.8027
- Rougelsum: 2.8035
## 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: 4
- eval_batch_size: 4
- seed: 42
- 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: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 23.6472 | 0.0160 | 5 | 11.7512 | 0.4881 | 0.0353 | 0.4380 | 0.4362 |
| 21.3789 | 0.0319 | 10 | 11.7109 | 0.4912 | 0.0353 | 0.4526 | 0.4486 |
| 19.719 | 0.0479 | 15 | 11.6279 | 0.5005 | 0.0432 | 0.4531 | 0.4477 |
| 22.2901 | 0.0639 | 20 | 11.6000 | 0.4946 | 0.0319 | 0.4410 | 0.4381 |
| 19.6455 | 0.0799 | 25 | 11.5404 | 0.5263 | 0.0530 | 0.4856 | 0.4833 |
| 19.892 | 0.0958 | 30 | 11.5011 | 0.5202 | 0.0396 | 0.4798 | 0.4716 |
| 19.8908 | 0.1118 | 35 | 11.4428 | 0.5431 | 0.0429 | 0.5013 | 0.4933 |
| 21.5179 | 0.1278 | 40 | 11.4066 | 0.5156 | 0.0405 | 0.4717 | 0.4682 |
| 21.7581 | 0.1438 | 45 | 11.3629 | 0.5416 | 0.0325 | 0.4834 | 0.4787 |
| 20.9988 | 0.1597 | 50 | 11.2869 | 0.5288 | 0.0270 | 0.4752 | 0.4743 |
| 21.3311 | 0.1757 | 55 | 11.2290 | 0.5260 | 0.0223 | 0.4642 | 0.4629 |
| 23.6669 | 0.1917 | 60 | 11.1785 | 0.4932 | 0.0188 | 0.4345 | 0.4307 |
| 18.2309 | 0.2077 | 65 | 11.1129 | 0.4645 | 0.0193 | 0.4156 | 0.4170 |
| 20.9785 | 0.2236 | 70 | 11.0331 | 0.5031 | 0.0238 | 0.4532 | 0.4530 |
| 16.4643 | 0.2396 | 75 | 10.9403 | 0.4414 | 0.0177 | 0.3945 | 0.3899 |
| 16.8242 | 0.2556 | 80 | 10.8374 | 0.4631 | 0.0177 | 0.4165 | 0.4110 |
| 23.1133 | 0.2716 | 85 | 10.7508 | 0.5054 | 0.0253 | 0.4434 | 0.4380 |
| 21.1076 | 0.2875 | 90 | 10.6718 | 0.4766 | 0.0178 | 0.4129 | 0.4101 |
| 17.6879 | 0.3035 | 95 | 10.5684 | 0.5166 | 0.0212 | 0.4634 | 0.4573 |
| 19.3182 | 0.3195 | 100 | 10.4315 | 0.5774 | 0.0217 | 0.5121 | 0.5070 |
| 18.6413 | 0.3355 | 105 | 10.2988 | 0.5325 | 0.0257 | 0.4803 | 0.4803 |
| 19.9276 | 0.3514 | 110 | 10.1745 | 0.5529 | 0.0348 | 0.4877 | 0.4841 |
| 17.9226 | 0.3674 | 115 | 10.0297 | 0.5852 | 0.0432 | 0.5075 | 0.5039 |
| 15.9707 | 0.3834 | 120 | 9.8977 | 0.5779 | 0.0403 | 0.5015 | 0.4992 |
| 16.5054 | 0.3994 | 125 | 9.7266 | 0.5685 | 0.0416 | 0.5011 | 0.4963 |
| 14.6994 | 0.4153 | 130 | 9.5595 | 0.6368 | 0.0506 | 0.5492 | 0.5447 |
| 15.9555 | 0.4313 | 135 | 9.3894 | 0.6401 | 0.0438 | 0.5520 | 0.5465 |
| 14.876 | 0.4473 | 140 | 9.2403 | 0.6910 | 0.0467 | 0.5961 | 0.5929 |
| 17.3615 | 0.4633 | 145 | 9.0976 | 0.7497 | 0.0499 | 0.6499 | 0.6448 |
| 15.8582 | 0.4792 | 150 | 8.9385 | 0.7409 | 0.0383 | 0.6427 | 0.6398 |
| 14.4111 | 0.4952 | 155 | 8.7924 | 0.7075 | 0.0457 | 0.6404 | 0.6366 |
| 13.9827 | 0.5112 | 160 | 8.6373 | 0.6750 | 0.0446 | 0.6211 | 0.6173 |
| 17.1081 | 0.5272 | 165 | 8.5070 | 0.7013 | 0.0547 | 0.6479 | 0.6420 |
| 14.2012 | 0.5431 | 170 | 8.3725 | 0.7220 | 0.0544 | 0.6553 | 0.6525 |
| 13.5024 | 0.5591 | 175 | 8.2316 | 0.7125 | 0.0324 | 0.6540 | 0.6495 |
| 13.2137 | 0.5751 | 180 | 8.1178 | 0.7591 | 0.0626 | 0.6776 | 0.6720 |
| 12.6791 | 0.5911 | 185 | 8.0139 | 0.7564 | 0.0302 | 0.6845 | 0.6840 |
| 13.4419 | 0.6070 | 190 | 7.9119 | 0.7047 | 0.0277 | 0.6559 | 0.6484 |
| 13.469 | 0.6230 | 195 | 7.8019 | 0.7849 | 0.0268 | 0.7215 | 0.7189 |
| 12.8491 | 0.6390 | 200 | 7.6875 | 0.8839 | 0.0264 | 0.8145 | 0.8153 |
| 12.8009 | 0.6550 | 205 | 7.5978 | 0.9797 | 0.0375 | 0.8922 | 0.8930 |
| 13.0495 | 0.6709 | 210 | 7.5245 | 1.0712 | 0.0504 | 0.9587 | 0.9579 |
| 12.3307 | 0.6869 | 215 | 7.4464 | 1.0918 | 0.0523 | 1.0047 | 0.9994 |
| 11.1893 | 0.7029 | 220 | 7.3770 | 1.1632 | 0.0695 | 1.0571 | 1.0527 |
| 12.0019 | 0.7188 | 225 | 7.3174 | 1.1872 | 0.0522 | 1.0827 | 1.0821 |
| 10.5739 | 0.7348 | 230 | 7.2509 | 1.1771 | 0.0665 | 1.0618 | 1.0630 |
| 10.7484 | 0.7508 | 235 | 7.1847 | 1.3403 | 0.0782 | 1.1967 | 1.1933 |
| 11.0539 | 0.7668 | 240 | 7.1230 | 1.4099 | 0.1009 | 1.2615 | 1.2612 |
| 10.6808 | 0.7827 | 245 | 7.0601 | 1.5268 | 0.0882 | 1.3528 | 1.3506 |
| 10.0456 | 0.7987 | 250 | 7.0148 | 1.4664 | 0.0789 | 1.3207 | 1.3142 |
| 9.7895 | 0.8147 | 255 | 6.9850 | 1.6529 | 0.0969 | 1.4578 | 1.4445 |
| 9.3146 | 0.8307 | 260 | 6.9547 | 1.7461 | 0.0943 | 1.5750 | 1.5566 |
| 9.8935 | 0.8466 | 265 | 6.9348 | 1.9384 | 0.1090 | 1.7219 | 1.7093 |
| 9.3272 | 0.8626 | 270 | 6.9348 | 1.8664 | 0.1143 | 1.6837 | 1.6758 |
| 9.4551 | 0.8786 | 275 | 6.9497 | 2.1360 | 0.1578 | 1.9404 | 1.9297 |
| 8.7474 | 0.8946 | 280 | 6.9095 | 2.1561 | 0.1494 | 1.9453 | 1.9398 |
| 8.8361 | 0.9105 | 285 | 6.8680 | 2.1476 | 0.1304 | 1.9360 | 1.9314 |
| 10.3327 | 0.9265 | 290 | 6.8129 | 2.2233 | 0.1330 | 1.9752 | 1.9732 |
| 9.6949 | 0.9425 | 295 | 6.7423 | 2.2698 | 0.1491 | 2.0114 | 2.0057 |
| 9.2422 | 0.9585 | 300 | 6.6728 | 2.2544 | 0.1332 | 2.0282 | 2.0281 |
| 9.1457 | 0.9744 | 305 | 6.5924 | 2.1699 | 0.1038 | 1.9641 | 1.9592 |
| 8.4371 | 0.9904 | 310 | 6.5061 | 2.2267 | 0.1423 | 2.0247 | 2.0174 |
| 8.8187 | 1.0064 | 315 | 6.4224 | 2.3070 | 0.1251 | 2.1206 | 2.1144 |
| 8.6228 | 1.0224 | 320 | 6.3316 | 2.3591 | 0.1070 | 2.1583 | 2.1714 |
| 7.9446 | 1.0383 | 325 | 6.2488 | 2.3552 | 0.1209 | 2.1538 | 2.1659 |
| 7.9126 | 1.0543 | 330 | 6.1856 | 2.3870 | 0.1292 | 2.1680 | 2.1668 |
| 8.0568 | 1.0703 | 335 | 6.1166 | 2.5029 | 0.1254 | 2.2559 | 2.2636 |
| 7.5392 | 1.0863 | 340 | 6.0326 | 2.4650 | 0.1265 | 2.2809 | 2.2768 |
| 8.2361 | 1.1022 | 345 | 5.9569 | 2.4594 | 0.1041 | 2.2155 | 2.2160 |
| 7.7452 | 1.1182 | 350 | 5.8964 | 2.4663 | 0.0998 | 2.2324 | 2.2333 |
| 7.6389 | 1.1342 | 355 | 5.8526 | 2.4997 | 0.1063 | 2.2902 | 2.2822 |
| 7.6098 | 1.1502 | 360 | 5.8106 | 2.6162 | 0.1157 | 2.3610 | 2.3596 |
| 7.8916 | 1.1661 | 365 | 5.7841 | 2.5536 | 0.0968 | 2.3276 | 2.3290 |
| 7.5782 | 1.1821 | 370 | 5.7585 | 2.5692 | 0.1032 | 2.3456 | 2.3406 |
| 7.3974 | 1.1981 | 375 | 5.7402 | 2.5963 | 0.1286 | 2.3806 | 2.3711 |
| 7.0614 | 1.2141 | 380 | 5.7159 | 2.6104 | 0.0990 | 2.3693 | 2.3758 |
| 7.2043 | 1.2300 | 385 | 5.6968 | 2.6200 | 0.0934 | 2.3816 | 2.3891 |
| 6.996 | 1.2460 | 390 | 5.6787 | 2.5952 | 0.0641 | 2.4221 | 2.4286 |
| 8.2705 | 1.2620 | 395 | 5.6632 | 2.6169 | 0.0403 | 2.4257 | 2.4329 |
| 7.1852 | 1.2780 | 400 | 5.6461 | 2.5815 | 0.0522 | 2.4163 | 2.4257 |
| 7.1047 | 1.2939 | 405 | 5.6273 | 2.5892 | 0.0486 | 2.4551 | 2.4584 |
| 7.0063 | 1.3099 | 410 | 5.6064 | 2.5683 | 0.0327 | 2.4328 | 2.4334 |
| 6.8297 | 1.3259 | 415 | 5.5840 | 2.5684 | 0.0425 | 2.4205 | 2.4136 |
| 6.7474 | 1.3419 | 420 | 5.5610 | 2.5945 | 0.0279 | 2.4552 | 2.4478 |
| 7.0426 | 1.3578 | 425 | 5.5415 | 2.5908 | 0.0120 | 2.4275 | 2.4241 |
| 6.6945 | 1.3738 | 430 | 5.5259 | 2.5609 | 0.0086 | 2.4019 | 2.4040 |
| 6.8208 | 1.3898 | 435 | 5.5160 | 2.6132 | 0.0086 | 2.4673 | 2.4634 |
| 6.6174 | 1.4058 | 440 | 5.5070 | 2.6443 | 0.0187 | 2.4737 | 2.4660 |
| 6.7205 | 1.4217 | 445 | 5.4988 | 2.6701 | 0.0236 | 2.5099 | 2.4985 |
| 6.6941 | 1.4377 | 450 | 5.4915 | 2.6858 | 0.0236 | 2.5133 | 2.5047 |
| 6.5988 | 1.4537 | 455 | 5.4851 | 2.6766 | 0.0349 | 2.5185 | 2.5128 |
| 6.4683 | 1.4696 | 460 | 5.4767 | 2.6661 | 0.0347 | 2.4922 | 2.4918 |
| 6.7409 | 1.4856 | 465 | 5.4675 | 2.6519 | 0.0347 | 2.5065 | 2.5077 |
| 6.9734 | 1.5016 | 470 | 5.4599 | 2.6663 | 0.0431 | 2.5285 | 2.5313 |
| 6.7049 | 1.5176 | 475 | 5.4536 | 2.6913 | 0.0428 | 2.5617 | 2.5574 |
| 7.1744 | 1.5335 | 480 | 5.4483 | 2.7426 | 0.0469 | 2.5896 | 2.5873 |
| 6.6163 | 1.5495 | 485 | 5.4434 | 2.7223 | 0.0428 | 2.5761 | 2.5782 |
| 6.6025 | 1.5655 | 490 | 5.4381 | 2.6981 | 0.0379 | 2.5405 | 2.5406 |
| 6.4328 | 1.5815 | 495 | 5.4326 | 2.6555 | 0.0321 | 2.5019 | 2.4957 |
| 6.5182 | 1.5974 | 500 | 5.4278 | 2.7413 | 0.0445 | 2.5816 | 2.5765 |
| 6.6248 | 1.6134 | 505 | 5.4226 | 2.7559 | 0.0384 | 2.5907 | 2.5833 |
| 6.4422 | 1.6294 | 510 | 5.4180 | 2.8097 | 0.0384 | 2.6591 | 2.6516 |
| 6.3315 | 1.6454 | 515 | 5.4139 | 2.8195 | 0.0345 | 2.6772 | 2.6692 |
| 6.3602 | 1.6613 | 520 | 5.4077 | 2.8024 | 0.0435 | 2.6610 | 2.6544 |
| 6.3096 | 1.6773 | 525 | 5.4016 | 2.8611 | 0.0558 | 2.7244 | 2.7161 |
| 6.4627 | 1.6933 | 530 | 5.3956 | 2.8914 | 0.0558 | 2.7576 | 2.7547 |
| 7.0027 | 1.7093 | 535 | 5.3912 | 2.9207 | 0.0601 | 2.7619 | 2.7592 |
| 6.6364 | 1.7252 | 540 | 5.3880 | 2.9260 | 0.0601 | 2.7612 | 2.7558 |
| 6.3329 | 1.7412 | 545 | 5.3835 | 2.9258 | 0.0631 | 2.7616 | 2.7580 |
| 6.3528 | 1.7572 | 550 | 5.3783 | 2.9378 | 0.0631 | 2.7630 | 2.7573 |
| 6.3083 | 1.7732 | 555 | 5.3731 | 2.9500 | 0.0631 | 2.7680 | 2.7632 |
| 6.3824 | 1.7891 | 560 | 5.3686 | 2.9599 | 0.0681 | 2.7896 | 2.7882 |
| 6.2145 | 1.8051 | 565 | 5.3646 | 2.9371 | 0.0644 | 2.7612 | 2.7619 |
| 6.5271 | 1.8211 | 570 | 5.3605 | 2.9350 | 0.0647 | 2.7695 | 2.7717 |
| 6.5508 | 1.8371 | 575 | 5.3568 | 2.9277 | 0.0524 | 2.7676 | 2.7682 |
| 6.4093 | 1.8530 | 580 | 5.3551 | 2.9401 | 0.0524 | 2.7711 | 2.7727 |
| 6.5111 | 1.8690 | 585 | 5.3532 | 2.9682 | 0.0641 | 2.7947 | 2.7934 |
| 6.459 | 1.8850 | 590 | 5.3513 | 2.9682 | 0.0641 | 2.7946 | 2.7933 |
| 6.3278 | 1.9010 | 595 | 5.3497 | 2.9685 | 0.0641 | 2.7994 | 2.7970 |
| 6.7423 | 1.9169 | 600 | 5.3486 | 2.9733 | 0.0641 | 2.7993 | 2.7969 |
| 6.5692 | 1.9329 | 605 | 5.3476 | 2.9732 | 0.0641 | 2.8092 | 2.8055 |
| 6.3758 | 1.9489 | 610 | 5.3467 | 2.9784 | 0.0640 | 2.8074 | 2.8060 |
| 6.4735 | 1.9649 | 615 | 5.3460 | 2.9749 | 0.0640 | 2.8028 | 2.8034 |
| 6.2938 | 1.9808 | 620 | 5.3455 | 2.9749 | 0.0640 | 2.8027 | 2.8033 |
| 6.2542 | 1.9968 | 625 | 5.3452 | 2.9750 | 0.0640 | 2.8027 | 2.8035 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0 |