
<!-- 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-small-finetuned-xsum

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5039
- Rouge1: 80.8002
- Rouge2: 77.6863
- Rougel: 80.6746
- Rougelsum: 80.7336
- Gen Len: 14.1393

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 150
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 113   | 0.7526          | 80.8695 | 77.9379 | 80.7636 | 80.7858   | 15.6577 |
| No log        | 2.0   | 226   | 0.6720          | 81.3067 | 78.4208 | 81.2158 | 81.2418   | 15.5721 |
| No log        | 3.0   | 339   | 0.6472          | 81.5539 | 78.6973 | 81.4666 | 81.5086   | 15.4799 |
| No log        | 4.0   | 452   | 0.6217          | 81.4038 | 78.5499 | 81.3074 | 81.3618   | 15.5369 |
| 0.7253        | 5.0   | 565   | 0.5931          | 81.6448 | 78.8248 | 81.5691 | 81.5943   | 15.4698 |
| 0.7253        | 6.0   | 678   | 0.5696          | 81.7034 | 78.8675 | 81.6142 | 81.64     | 15.453  |
| 0.7253        | 7.0   | 791   | 0.5646          | 81.7875 | 78.9862 | 81.727  | 81.7454   | 15.4329 |
| 0.7253        | 8.0   | 904   | 0.5531          | 81.7309 | 78.905  | 81.6487 | 81.6755   | 15.4346 |
| 0.5664        | 9.0   | 1017  | 0.5409          | 81.5895 | 78.7604 | 81.4983 | 81.5348   | 15.4178 |
| 0.5664        | 10.0  | 1130  | 0.5467          | 81.5002 | 78.6385 | 81.3915 | 81.4247   | 15.448  |
| 0.5664        | 11.0  | 1243  | 0.5290          | 81.622  | 78.7775 | 81.5339 | 81.5417   | 15.4128 |
| 0.5664        | 12.0  | 1356  | 0.5247          | 81.5904 | 78.7444 | 81.4944 | 81.5451   | 15.3641 |
| 0.5664        | 13.0  | 1469  | 0.5164          | 81.6429 | 78.8116 | 81.5581 | 81.5926   | 15.3574 |
| 0.499         | 14.0  | 1582  | 0.5182          | 81.5478 | 78.6836 | 81.455  | 81.5058   | 15.3607 |
| 0.499         | 15.0  | 1695  | 0.5058          | 81.4959 | 78.6553 | 81.4129 | 81.4608   | 15.2433 |
| 0.499         | 16.0  | 1808  | 0.4985          | 81.7445 | 78.971  | 81.6587 | 81.7184   | 15.1913 |
| 0.499         | 17.0  | 1921  | 0.4953          | 81.6383 | 78.8217 | 81.5419 | 81.6169   | 15.2131 |
| 0.456         | 18.0  | 2034  | 0.4914          | 81.6345 | 78.8308 | 81.506  | 81.5956   | 15.1695 |
| 0.456         | 19.0  | 2147  | 0.4918          | 81.4352 | 78.6371 | 81.319  | 81.4134   | 15.0923 |
| 0.456         | 20.0  | 2260  | 0.4950          | 81.4993 | 78.6787 | 81.401  | 81.466    | 15.1661 |
| 0.456         | 21.0  | 2373  | 0.4839          | 81.7538 | 78.9501 | 81.655  | 81.7017   | 15.0453 |
| 0.456         | 22.0  | 2486  | 0.4917          | 81.445  | 78.6264 | 81.3378 | 81.4072   | 15.1376 |
| 0.4233        | 23.0  | 2599  | 0.4790          | 81.6857 | 78.8888 | 81.5719 | 81.6151   | 15.0084 |
| 0.4233        | 24.0  | 2712  | 0.4801          | 81.5146 | 78.7124 | 81.3956 | 81.4622   | 15.047  |
| 0.4233        | 25.0  | 2825  | 0.4833          | 81.4409 | 78.6415 | 81.3185 | 81.4137   | 15.0587 |
| 0.4233        | 26.0  | 2938  | 0.4846          | 81.4886 | 78.6912 | 81.3758 | 81.4498   | 15.0487 |
| 0.396         | 27.0  | 3051  | 0.4782          | 81.4474 | 78.6254 | 81.3355 | 81.4372   | 14.8674 |
| 0.396         | 28.0  | 3164  | 0.4767          | 81.5577 | 78.7259 | 81.4474 | 81.4906   | 14.7919 |
| 0.396         | 29.0  | 3277  | 0.4745          | 81.648  | 78.7893 | 81.5163 | 81.5654   | 14.9262 |
| 0.396         | 30.0  | 3390  | 0.4679          | 81.4867 | 78.6765 | 81.3659 | 81.4438   | 14.7399 |
| 0.3738        | 31.0  | 3503  | 0.4722          | 81.8409 | 79.0512 | 81.7436 | 81.7752   | 15.0    |
| 0.3738        | 32.0  | 3616  | 0.4698          | 81.6546 | 78.867  | 81.5383 | 81.6146   | 14.9279 |
| 0.3738        | 33.0  | 3729  | 0.4629          | 81.5223 | 78.6672 | 81.3989 | 81.4953   | 14.6342 |
| 0.3738        | 34.0  | 3842  | 0.4689          | 81.3717 | 78.4879 | 81.2359 | 81.3315   | 14.7534 |
| 0.3738        | 35.0  | 3955  | 0.4714          | 81.4911 | 78.6664 | 81.3923 | 81.4424   | 14.8842 |
| 0.3585        | 36.0  | 4068  | 0.4615          | 81.2428 | 78.3459 | 81.1102 | 81.1907   | 14.4581 |
| 0.3585        | 37.0  | 4181  | 0.4709          | 81.4039 | 78.4899 | 81.2677 | 81.3251   | 14.7299 |
| 0.3585        | 38.0  | 4294  | 0.4723          | 81.4856 | 78.6036 | 81.3627 | 81.4373   | 14.8154 |
| 0.3585        | 39.0  | 4407  | 0.4704          | 81.3924 | 78.5321 | 81.3295 | 81.3834   | 14.6158 |
| 0.3377        | 40.0  | 4520  | 0.4649          | 81.4455 | 78.5817 | 81.3635 | 81.4353   | 14.5906 |
| 0.3377        | 41.0  | 4633  | 0.4646          | 81.2935 | 78.4222 | 81.1972 | 81.2504   | 14.4983 |
| 0.3377        | 42.0  | 4746  | 0.4692          | 81.2082 | 78.3097 | 81.1218 | 81.18     | 14.5872 |
| 0.3377        | 43.0  | 4859  | 0.4673          | 81.3108 | 78.426  | 81.2192 | 81.2795   | 14.5822 |
| 0.3377        | 44.0  | 4972  | 0.4763          | 81.1511 | 78.272  | 81.0806 | 81.1195   | 14.6174 |
| 0.327         | 45.0  | 5085  | 0.4703          | 81.1883 | 78.2662 | 81.0751 | 81.1556   | 14.5017 |
| 0.327         | 46.0  | 5198  | 0.4701          | 81.3512 | 78.497  | 81.2556 | 81.2958   | 14.5638 |
| 0.327         | 47.0  | 5311  | 0.4675          | 81.3069 | 78.4365 | 81.2282 | 81.2661   | 14.5872 |
| 0.327         | 48.0  | 5424  | 0.4713          | 81.3203 | 78.4676 | 81.2704 | 81.2963   | 14.6074 |
| 0.3132        | 49.0  | 5537  | 0.4685          | 81.4914 | 78.6478 | 81.4025 | 81.4461   | 14.5319 |
| 0.3132        | 50.0  | 5650  | 0.4704          | 81.4722 | 78.6349 | 81.401  | 81.4166   | 14.5185 |
| 0.3132        | 51.0  | 5763  | 0.4746          | 81.5848 | 78.7389 | 81.4983 | 81.5228   | 14.5487 |
| 0.3132        | 52.0  | 5876  | 0.4736          | 81.6095 | 78.7901 | 81.5205 | 81.5296   | 14.5101 |
| 0.3132        | 53.0  | 5989  | 0.4738          | 81.4913 | 78.6738 | 81.3957 | 81.4394   | 14.5956 |
| 0.3043        | 54.0  | 6102  | 0.4733          | 81.3817 | 78.4843 | 81.2916 | 81.3222   | 14.6795 |
| 0.3043        | 55.0  | 6215  | 0.4747          | 81.4791 | 78.5596 | 81.3719 | 81.391    | 14.6023 |
| 0.3043        | 56.0  | 6328  | 0.4755          | 81.3834 | 78.4865 | 81.3217 | 81.334    | 14.5537 |
| 0.3043        | 57.0  | 6441  | 0.4687          | 81.0989 | 78.1685 | 81.0179 | 81.0713   | 14.3742 |
| 0.3           | 58.0  | 6554  | 0.4746          | 81.5527 | 78.6533 | 81.4764 | 81.5086   | 14.4933 |
| 0.3           | 59.0  | 6667  | 0.4717          | 81.4294 | 78.5367 | 81.3555 | 81.393    | 14.3842 |
| 0.3           | 60.0  | 6780  | 0.4797          | 81.2638 | 78.347  | 81.1945 | 81.2258   | 14.5906 |
| 0.3           | 61.0  | 6893  | 0.4740          | 81.2198 | 78.3272 | 81.1701 | 81.1926   | 14.5151 |
| 0.2835        | 62.0  | 7006  | 0.4742          | 81.1578 | 78.2664 | 81.0988 | 81.1239   | 14.5218 |
| 0.2835        | 63.0  | 7119  | 0.4766          | 81.0438 | 78.1511 | 80.9756 | 81.0192   | 14.4312 |
| 0.2835        | 64.0  | 7232  | 0.4716          | 80.967  | 78.013  | 80.8988 | 80.9291   | 14.2936 |
| 0.2835        | 65.0  | 7345  | 0.4729          | 81.0833 | 78.16   | 81.0197 | 81.0557   | 14.3221 |
| 0.2835        | 66.0  | 7458  | 0.4788          | 81.1509 | 78.2452 | 81.0636 | 81.1082   | 14.4396 |
| 0.2753        | 67.0  | 7571  | 0.4802          | 81.2766 | 78.3662 | 81.1998 | 81.2395   | 14.4362 |
| 0.2753        | 68.0  | 7684  | 0.4764          | 80.986  | 78.0241 | 80.907  | 80.9182   | 14.4295 |
| 0.2753        | 69.0  | 7797  | 0.4783          | 81.2485 | 78.3734 | 81.1851 | 81.232    | 14.4178 |
| 0.2753        | 70.0  | 7910  | 0.4794          | 81.1969 | 78.2884 | 81.1091 | 81.1547   | 14.3943 |
| 0.2671        | 71.0  | 8023  | 0.4746          | 81.1233 | 78.1151 | 81.0474 | 81.1019   | 14.307  |
| 0.2671        | 72.0  | 8136  | 0.4750          | 81.0761 | 78.1707 | 80.99   | 81.0476   | 14.3758 |
| 0.2671        | 73.0  | 8249  | 0.4769          | 81.1251 | 78.1659 | 81.0612 | 81.1      | 14.3876 |
| 0.2671        | 74.0  | 8362  | 0.4809          | 81.1335 | 78.2075 | 81.0582 | 81.1128   | 14.3909 |
| 0.2671        | 75.0  | 8475  | 0.4819          | 81.1342 | 78.2138 | 81.0627 | 81.0962   | 14.4866 |
| 0.2611        | 76.0  | 8588  | 0.4779          | 81.1457 | 78.2469 | 81.0921 | 81.1249   | 14.4228 |
| 0.2611        | 77.0  | 8701  | 0.4849          | 81.3577 | 78.4481 | 81.2961 | 81.3106   | 14.4916 |
| 0.2611        | 78.0  | 8814  | 0.4854          | 81.2655 | 78.3525 | 81.2021 | 81.2204   | 14.4379 |
| 0.2611        | 79.0  | 8927  | 0.4779          | 81.209  | 78.2182 | 81.1394 | 81.2018   | 14.3104 |
| 0.2582        | 80.0  | 9040  | 0.4792          | 81.1094 | 78.109  | 81.0498 | 81.0597   | 14.443  |
| 0.2582        | 81.0  | 9153  | 0.4798          | 81.2118 | 78.2388 | 81.158  | 81.1979   | 14.2836 |
| 0.2582        | 82.0  | 9266  | 0.4785          | 81.1646 | 78.1741 | 81.0892 | 81.1318   | 14.2819 |
| 0.2582        | 83.0  | 9379  | 0.4894          | 81.0246 | 78.0386 | 80.9799 | 81.0082   | 14.5352 |
| 0.2582        | 84.0  | 9492  | 0.4852          | 80.8181 | 77.748  | 80.7271 | 80.7857   | 14.307  |
| 0.2502        | 85.0  | 9605  | 0.4853          | 80.8607 | 77.8081 | 80.7819 | 80.826    | 14.2819 |
| 0.2502        | 86.0  | 9718  | 0.4821          | 81.0753 | 78.0443 | 80.977  | 81.0585   | 14.1628 |
| 0.2502        | 87.0  | 9831  | 0.4836          | 81.0502 | 78.0125 | 80.9437 | 81.0227   | 14.1829 |
| 0.2502        | 88.0  | 9944  | 0.4867          | 81.0832 | 78.0581 | 80.9885 | 81.0629   | 14.2232 |
| 0.2474        | 89.0  | 10057 | 0.4885          | 80.8361 | 77.8075 | 80.7644 | 80.8113   | 14.245  |
| 0.2474        | 90.0  | 10170 | 0.4926          | 80.9648 | 77.9656 | 80.8858 | 80.9429   | 14.3758 |
| 0.2474        | 91.0  | 10283 | 0.4862          | 81.0499 | 77.9909 | 80.9529 | 81.0251   | 14.1594 |
| 0.2474        | 92.0  | 10396 | 0.4885          | 80.9683 | 77.9313 | 80.8599 | 80.9175   | 14.2735 |
| 0.2381        | 93.0  | 10509 | 0.4858          | 80.964  | 77.9419 | 80.8997 | 80.9494   | 14.3272 |
| 0.2381        | 94.0  | 10622 | 0.4891          | 80.7479 | 77.6563 | 80.6516 | 80.7074   | 14.3993 |
| 0.2381        | 95.0  | 10735 | 0.4909          | 80.7166 | 77.5902 | 80.5996 | 80.6605   | 14.2651 |
| 0.2381        | 96.0  | 10848 | 0.4845          | 81.174  | 78.0743 | 81.0369 | 81.0988   | 14.099  |
| 0.2381        | 97.0  | 10961 | 0.4886          | 80.8086 | 77.7071 | 80.7341 | 80.7905   | 14.2131 |
| 0.2387        | 98.0  | 11074 | 0.4932          | 80.8045 | 77.7326 | 80.7178 | 80.767    | 14.4245 |
| 0.2387        | 99.0  | 11187 | 0.4890          | 80.8664 | 77.7815 | 80.7817 | 80.8381   | 14.2886 |
| 0.2387        | 100.0 | 11300 | 0.4843          | 80.742  | 77.6378 | 80.636  | 80.6881   | 13.9463 |
| 0.2387        | 101.0 | 11413 | 0.4900          | 80.5951 | 77.4218 | 80.4692 | 80.5166   | 14.2131 |
| 0.2343        | 102.0 | 11526 | 0.4933          | 80.9176 | 77.8813 | 80.7994 | 80.8637   | 14.2047 |
| 0.2343        | 103.0 | 11639 | 0.4936          | 80.8901 | 77.8476 | 80.7945 | 80.8447   | 14.1812 |
| 0.2343        | 104.0 | 11752 | 0.4955          | 80.9422 | 77.9055 | 80.8414 | 80.8666   | 14.2634 |
| 0.2343        | 105.0 | 11865 | 0.4971          | 80.9296 | 77.8819 | 80.8107 | 80.8588   | 14.2617 |
| 0.2343        | 106.0 | 11978 | 0.4968          | 80.8841 | 77.8315 | 80.7829 | 80.8081   | 14.2735 |
| 0.2309        | 107.0 | 12091 | 0.4949          | 80.8845 | 77.831  | 80.766  | 80.8197   | 14.1862 |
| 0.2309        | 108.0 | 12204 | 0.4979          | 80.817  | 77.77   | 80.7009 | 80.7623   | 14.3104 |
| 0.2309        | 109.0 | 12317 | 0.4970          | 80.9426 | 77.884  | 80.8245 | 80.8849   | 14.1862 |
| 0.2309        | 110.0 | 12430 | 0.4951          | 80.8217 | 77.7436 | 80.7137 | 80.7638   | 14.2181 |
| 0.225         | 111.0 | 12543 | 0.4971          | 80.9686 | 77.908  | 80.8479 | 80.8945   | 14.1846 |
| 0.225         | 112.0 | 12656 | 0.4998          | 80.7005 | 77.6143 | 80.5708 | 80.6458   | 14.1711 |
| 0.225         | 113.0 | 12769 | 0.5010          | 80.6586 | 77.5568 | 80.5494 | 80.6194   | 14.0872 |
| 0.225         | 114.0 | 12882 | 0.5020          | 80.5762 | 77.4938 | 80.4571 | 80.5458   | 14.2013 |
| 0.225         | 115.0 | 12995 | 0.4950          | 80.7756 | 77.6717 | 80.6326 | 80.7221   | 14.0671 |
| 0.2248        | 116.0 | 13108 | 0.4974          | 80.6474 | 77.5174 | 80.5385 | 80.5867   | 14.1527 |
| 0.2248        | 117.0 | 13221 | 0.5002          | 80.6698 | 77.5889 | 80.5657 | 80.6265   | 14.2567 |
| 0.2248        | 118.0 | 13334 | 0.4998          | 80.5252 | 77.4293 | 80.4052 | 80.4697   | 14.2466 |
| 0.2248        | 119.0 | 13447 | 0.4994          | 80.4945 | 77.381  | 80.4047 | 80.4778   | 14.1527 |
| 0.2244        | 120.0 | 13560 | 0.5007          | 80.687  | 77.5655 | 80.5506 | 80.6345   | 14.0889 |
| 0.2244        | 121.0 | 13673 | 0.5003          | 80.6725 | 77.5569 | 80.5444 | 80.6284   | 14.0889 |
| 0.2244        | 122.0 | 13786 | 0.5012          | 80.5519 | 77.4681 | 80.4309 | 80.5167   | 14.2064 |
| 0.2244        | 123.0 | 13899 | 0.4984          | 80.5439 | 77.4156 | 80.4356 | 80.5053   | 14.1091 |
| 0.2142        | 124.0 | 14012 | 0.5003          | 80.506  | 77.3663 | 80.3909 | 80.4609   | 14.1258 |
| 0.2142        | 125.0 | 14125 | 0.5012          | 80.5929 | 77.47   | 80.4856 | 80.5471   | 14.1057 |
| 0.2142        | 126.0 | 14238 | 0.5015          | 80.8261 | 77.7005 | 80.7021 | 80.7576   | 14.1846 |
| 0.2142        | 127.0 | 14351 | 0.4989          | 80.7286 | 77.6025 | 80.6101 | 80.6584   | 14.1309 |
| 0.2142        | 128.0 | 14464 | 0.4995          | 80.7703 | 77.6574 | 80.6209 | 80.7013   | 14.2047 |
| 0.2239        | 129.0 | 14577 | 0.5030          | 80.7682 | 77.6334 | 80.6326 | 80.7075   | 14.2685 |
| 0.2239        | 130.0 | 14690 | 0.5017          | 80.8383 | 77.7289 | 80.7019 | 80.7832   | 14.1997 |
| 0.2239        | 131.0 | 14803 | 0.5007          | 80.8551 | 77.7449 | 80.7238 | 80.7909   | 14.1359 |
| 0.2239        | 132.0 | 14916 | 0.5004          | 80.9042 | 77.8065 | 80.762  | 80.8351   | 14.1191 |
| 0.2139        | 133.0 | 15029 | 0.5001          | 80.9345 | 77.8301 | 80.784  | 80.8658   | 14.1107 |
| 0.2139        | 134.0 | 15142 | 0.5023          | 80.8865 | 77.7869 | 80.7474 | 80.8159   | 14.1174 |
| 0.2139        | 135.0 | 15255 | 0.5036          | 80.8305 | 77.7027 | 80.709  | 80.7658   | 14.1812 |
| 0.2139        | 136.0 | 15368 | 0.5027          | 80.8305 | 77.7027 | 80.709  | 80.7658   | 14.1812 |
| 0.2139        | 137.0 | 15481 | 0.5029          | 80.801  | 77.6711 | 80.6703 | 80.7443   | 14.1862 |
| 0.2152        | 138.0 | 15594 | 0.5022          | 80.9639 | 77.8473 | 80.8252 | 80.8959   | 14.1544 |
| 0.2152        | 139.0 | 15707 | 0.5033          | 80.9216 | 77.8092 | 80.7903 | 80.8622   | 14.1594 |
| 0.2152        | 140.0 | 15820 | 0.5034          | 80.8977 | 77.7878 | 80.7642 | 80.8317   | 14.1628 |
| 0.2152        | 141.0 | 15933 | 0.5030          | 80.8977 | 77.7878 | 80.7642 | 80.8317   | 14.1628 |
| 0.2187        | 142.0 | 16046 | 0.5024          | 80.6562 | 77.5245 | 80.5202 | 80.6065   | 14.0923 |
| 0.2187        | 143.0 | 16159 | 0.5031          | 80.8168 | 77.7025 | 80.686  | 80.7553   | 14.1326 |
| 0.2187        | 144.0 | 16272 | 0.5031          | 80.6336 | 77.4867 | 80.4892 | 80.5611   | 14.1023 |
| 0.2187        | 145.0 | 16385 | 0.5038          | 80.8002 | 77.6863 | 80.6746 | 80.7336   | 14.1393 |
| 0.2187        | 146.0 | 16498 | 0.5040          | 80.8977 | 77.7878 | 80.7642 | 80.8317   | 14.1628 |
| 0.2166        | 147.0 | 16611 | 0.5039          | 80.8977 | 77.7878 | 80.7642 | 80.8317   | 14.1628 |
| 0.2166        | 148.0 | 16724 | 0.5038          | 80.8002 | 77.6863 | 80.6746 | 80.7336   | 14.1393 |
| 0.2166        | 149.0 | 16837 | 0.5039          | 80.8002 | 77.6863 | 80.6746 | 80.7336   | 14.1393 |
| 0.2166        | 150.0 | 16950 | 0.5039          | 80.8002 | 77.6863 | 80.6746 | 80.7336   | 14.1393 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "t5-small-finetuned-xsum", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small-finetuned-xsum
=======================


This model is a fine-tuned version of t5-small on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5039
* Rouge1: 80.8002
* Rouge2: 77.6863
* Rougel: 80.6746
* Rougelsum: 80.7336
* Gen Len: 14.1393


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: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 150
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 150
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 150
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 150
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2