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t5-base-finetuned-xsum
javedonline/t5-base-finetuned-xsum
t5-base-finetuned-xsum is a machine learning model from javedonline. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Mar 4, 2025
- Updated
- Mar 17, 2025
- SHA
- e55d0a8b
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
t5-base-finetuned-xsum
This model is a fine-tuned version of google-t5/t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9364
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: 16
- eval_batch_size: 16
- 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: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 41 | 3.2887 |
| No log | 2.0 | 82 | 2.9086 |
| No log | 3.0 | 123 | 2.7011 |
| No log | 4.0 | 164 | 2.5602 |
| No log | 5.0 | 205 | 2.4619 |
| No log | 6.0 | 246 | 2.3696 |
| No log | 7.0 | 287 | 2.2853 |
| No log | 8.0 | 328 | 2.2141 |
| No log | 9.0 | 369 | 2.1824 |
| No log | 10.0 | 410 | 2.1532 |
| No log | 11.0 | 451 | 2.1143 |
| No log | 12.0 | 492 | 2.1041 |
| 2.6836 | 13.0 | 533 | 2.0784 |
| 2.6836 | 14.0 | 574 | 2.0637 |
| 2.6836 | 15.0 | 615 | 2.0414 |
| 2.6836 | 16.0 | 656 | 2.0277 |
| 2.6836 | 17.0 | 697 | 2.0193 |
| 2.6836 | 18.0 | 738 | 2.0077 |
| 2.6836 | 19.0 | 779 | 1.9936 |
| 2.6836 | 20.0 | 820 | 1.9888 |
| 2.6836 | 21.0 | 861 | 1.9786 |
| 2.6836 | 22.0 | 902 | 1.9749 |
| 2.6836 | 23.0 | 943 | 1.9674 |
| 2.6836 | 24.0 | 984 | 1.9617 |
| 1.911 | 25.0 | 1025 | 1.9517 |
| 1.911 | 26.0 | 1066 | 1.9506 |
| 1.911 | 27.0 | 1107 | 1.9456 |
| 1.911 | 28.0 | 1148 | 1.9381 |
| 1.911 | 29.0 | 1189 | 1.9304 |
| 1.911 | 30.0 | 1230 | 1.9324 |
| 1.911 | 31.0 | 1271 | 1.9278 |
| 1.911 | 32.0 | 1312 | 1.9302 |
| 1.911 | 33.0 | 1353 | 1.9259 |
| 1.911 | 34.0 | 1394 | 1.9242 |
| 1.911 | 35.0 | 1435 | 1.9245 |
| 1.911 | 36.0 | 1476 | 1.9197 |
| 1.6731 | 37.0 | 1517 | 1.9282 |
| 1.6731 | 38.0 | 1558 | 1.9208 |
| 1.6731 | 39.0 | 1599 | 1.9186 |
| 1.6731 | 40.0 | 1640 | 1.9220 |
| 1.6731 | 41.0 | 1681 | 1.9163 |
| 1.6731 | 42.0 | 1722 | 1.9212 |
| 1.6731 | 43.0 | 1763 | 1.9197 |
| 1.6731 | 44.0 | 1804 | 1.9185 |
| 1.6731 | 45.0 | 1845 | 1.9150 |
| 1.6731 | 46.0 | 1886 | 1.9163 |
| 1.6731 | 47.0 | 1927 | 1.9189 |
| 1.6731 | 48.0 | 1968 | 1.9161 |
| 1.5274 | 49.0 | 2009 | 1.9177 |
| 1.5274 | 50.0 | 2050 | 1.9145 |
| 1.5274 | 51.0 | 2091 | 1.9128 |
| 1.5274 | 52.0 | 2132 | 1.9165 |
| 1.5274 | 53.0 | 2173 | 1.9147 |
| 1.5274 | 54.0 | 2214 | 1.9196 |
| 1.5274 | 55.0 | 2255 | 1.9153 |
| 1.5274 | 56.0 | 2296 | 1.9184 |
| 1.5274 | 57.0 | 2337 | 1.9180 |
| 1.5274 | 58.0 | 2378 | 1.9173 |
| 1.5274 | 59.0 | 2419 | 1.9174 |
| 1.5274 | 60.0 | 2460 | 1.9173 |
| 1.4337 | 61.0 | 2501 | 1.9168 |
| 1.4337 | 62.0 | 2542 | 1.9219 |
| 1.4337 | 63.0 | 2583 | 1.9240 |
| 1.4337 | 64.0 | 2624 | 1.9220 |
| 1.4337 | 65.0 | 2665 | 1.9210 |
| 1.4337 | 66.0 | 2706 | 1.9252 |
| 1.4337 | 67.0 | 2747 | 1.9237 |
| 1.4337 | 68.0 | 2788 | 1.9257 |
| 1.4337 | 69.0 | 2829 | 1.9314 |
| 1.4337 | 70.0 | 2870 | 1.9329 |
| 1.4337 | 71.0 | 2911 | 1.9351 |
| 1.4337 | 72.0 | 2952 | 1.9332 |
| 1.4337 | 73.0 | 2993 | 1.9276 |
| 1.3641 | 74.0 | 3034 | 1.9290 |
| 1.3641 | 75.0 | 3075 | 1.9330 |
| 1.3641 | 76.0 | 3116 | 1.9350 |
| 1.3641 | 77.0 | 3157 | 1.9351 |
| 1.3641 | 78.0 | 3198 | 1.9332 |
| 1.3641 | 79.0 | 3239 | 1.9326 |
| 1.3641 | 80.0 | 3280 | 1.9315 |
| 1.3641 | 81.0 | 3321 | 1.9332 |
| 1.3641 | 82.0 | 3362 | 1.9320 |
| 1.3641 | 83.0 | 3403 | 1.9344 |
| 1.3641 | 84.0 | 3444 | 1.9367 |
| 1.3641 | 85.0 | 3485 | 1.9374 |
| 1.3238 | 86.0 | 3526 | 1.9340 |
| 1.3238 | 87.0 | 3567 | 1.9340 |
| 1.3238 | 88.0 | 3608 | 1.9330 |
| 1.3238 | 89.0 | 3649 | 1.9335 |
| 1.3238 | 90.0 | 3690 | 1.9336 |
| 1.3238 | 91.0 | 3731 | 1.9355 |
| 1.3238 | 92.0 | 3772 | 1.9361 |
| 1.3238 | 93.0 | 3813 | 1.9366 |
| 1.3238 | 94.0 | 3854 | 1.9369 |
| 1.3238 | 95.0 | 3895 | 1.9362 |
| 1.3238 | 96.0 | 3936 | 1.9365 |
| 1.3238 | 97.0 | 3977 | 1.9366 |
| 1.3042 | 98.0 | 4018 | 1.9367 |
| 1.3042 | 99.0 | 4059 | 1.9364 |
| 1.3042 | 100.0 | 4100 | 1.9364 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu118
- Datasets 3.3.1
- Tokenizers 0.21.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Mar 4, 2025
- Updated
- Mar 17, 2025