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t5-small-mse-summarization

Text2Text Generation
Transformers
PyTorch
TensorBoard
t5
Generated from Trainer
text-generation-inference
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update model card README.md

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@@ -16,13 +16,13 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2293
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- - Rouge1: 40.0683
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- - Rouge2: 20.2468
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- - Rougel: 34.0606
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- - Rougelsum: 38.0836
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- - Bleurt: -0.8806
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- - Gen Len: 18.649
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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  - train_batch_size: 64
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  - eval_batch_size: 256
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  - seed: 42
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleurt | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|
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- | 1.768 | 1.0 | 267 | 1.4680 | 36.028 | 16.6997 | 30.4417 | 33.8528 | -0.9554 | 18.557 |
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- | 1.5588 | 2.0 | 534 | 1.3877 | 37.4937 | 18.2652 | 32.1414 | 35.621 | -0.9248 | 18.646 |
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- | 1.503 | 3.0 | 801 | 1.3469 | 38.1407 | 18.7353 | 32.5747 | 36.3185 | -0.9069 | 18.649 |
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- | 1.4721 | 4.0 | 1068 | 1.3226 | 38.1918 | 18.5221 | 32.4574 | 36.3975 | -0.9071 | 18.661 |
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- | 1.4402 | 5.0 | 1335 | 1.3061 | 38.672 | 18.8355 | 32.734 | 36.7534 | -0.9074 | 18.696 |
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- | 1.4141 | 6.0 | 1602 | 1.2909 | 38.9248 | 19.0159 | 33.0053 | 36.98 | -0.9066 | 18.677 |
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- | 1.4034 | 7.0 | 1869 | 1.2779 | 39.3301 | 19.2995 | 33.2336 | 37.3958 | -0.9047 | 18.68 |
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- | 1.3864 | 8.0 | 2136 | 1.2686 | 39.5046 | 19.5836 | 33.4436 | 37.46 | -0.8928 | 18.681 |
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- | 1.3801 | 9.0 | 2403 | 1.2599 | 39.6226 | 19.6625 | 33.6596 | 37.6379 | -0.8954 | 18.686 |
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- | 1.3714 | 10.0 | 2670 | 1.2555 | 39.4381 | 19.5523 | 33.4644 | 37.4258 | -0.8983 | 18.721 |
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- | 1.3586 | 11.0 | 2937 | 1.2493 | 39.6582 | 19.7031 | 33.5629 | 37.5895 | -0.8951 | 18.707 |
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- | 1.3482 | 12.0 | 3204 | 1.2436 | 39.6473 | 19.6636 | 33.631 | 37.643 | -0.8945 | 18.7 |
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- | 1.3448 | 13.0 | 3471 | 1.2407 | 39.6741 | 19.686 | 33.6859 | 37.6884 | -0.8922 | 18.661 |
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- | 1.3458 | 14.0 | 3738 | 1.2382 | 39.7934 | 19.879 | 33.8368 | 37.8078 | -0.8863 | 18.658 |
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- | 1.3315 | 15.0 | 4005 | 1.2343 | 39.812 | 19.935 | 33.8546 | 37.8262 | -0.8859 | 18.666 |
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- | 1.3374 | 16.0 | 4272 | 1.2335 | 39.7989 | 19.9576 | 33.8681 | 37.803 | -0.885 | 18.657 |
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- | 1.3301 | 17.0 | 4539 | 1.2315 | 39.9386 | 20.0602 | 33.941 | 37.9452 | -0.8853 | 18.656 |
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- | 1.3295 | 18.0 | 4806 | 1.2303 | 40.0492 | 20.1841 | 34.0707 | 38.0749 | -0.8823 | 18.651 |
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- | 1.3284 | 19.0 | 5073 | 1.2294 | 40.0335 | 20.2042 | 34.061 | 38.0575 | -0.881 | 18.649 |
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- | 1.3249 | 20.0 | 5340 | 1.2293 | 40.0683 | 20.2468 | 34.0606 | 38.0836 | -0.8806 | 18.649 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1108
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+ - Rouge1: 43.1145
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+ - Rouge2: 23.2262
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+ - Rougel: 37.218
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+ - Rougelsum: 41.0897
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+ - Bleurt: -0.8051
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+ - Gen Len: 18.549
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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  - train_batch_size: 64
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  - eval_batch_size: 256
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleurt | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|
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+ | 1.5207 | 1.0 | 267 | 1.2922 | 38.8738 | 19.1958 | 32.8458 | 36.9993 | -0.9061 | 18.668 |
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+ | 1.363 | 2.0 | 534 | 1.2340 | 39.8466 | 20.0452 | 33.9101 | 37.7708 | -0.8925 | 18.657 |
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+ | 1.3062 | 3.0 | 801 | 1.2057 | 40.5536 | 20.8249 | 34.5221 | 38.4648 | -0.8625 | 18.602 |
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+ | 1.272 | 4.0 | 1068 | 1.1782 | 41.0078 | 21.2186 | 35.0101 | 38.9186 | -0.8595 | 18.602 |
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+ | 1.2312 | 5.0 | 1335 | 1.1688 | 41.521 | 21.7934 | 35.704 | 39.4718 | -0.842 | 18.486 |
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+ | 1.2052 | 6.0 | 1602 | 1.1557 | 42.1037 | 22.4291 | 36.3554 | 40.1124 | -0.8432 | 18.533 |
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+ | 1.1842 | 7.0 | 1869 | 1.1440 | 42.4438 | 22.6456 | 36.5729 | 40.3134 | -0.8288 | 18.553 |
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+ | 1.1643 | 8.0 | 2136 | 1.1408 | 42.245 | 22.4859 | 36.3637 | 40.2193 | -0.8284 | 18.622 |
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+ | 1.1495 | 9.0 | 2403 | 1.1320 | 42.5362 | 22.5034 | 36.5092 | 40.4552 | -0.8211 | 18.57 |
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+ | 1.1368 | 10.0 | 2670 | 1.1301 | 42.5159 | 22.462 | 36.4646 | 40.3968 | -0.819 | 18.538 |
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+ | 1.1203 | 11.0 | 2937 | 1.1243 | 42.2803 | 22.5963 | 36.3454 | 40.2987 | -0.8242 | 18.522 |
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+ | 1.1116 | 12.0 | 3204 | 1.1197 | 42.8078 | 22.8409 | 36.7344 | 40.8186 | -0.821 | 18.565 |
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+ | 1.099 | 13.0 | 3471 | 1.1193 | 42.7423 | 22.9397 | 36.7894 | 40.7298 | -0.8125 | 18.552 |
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+ | 1.0976 | 14.0 | 3738 | 1.1176 | 42.9002 | 23.2394 | 37.0215 | 40.9211 | -0.8156 | 18.568 |
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+ | 1.0816 | 15.0 | 4005 | 1.1133 | 43.0007 | 23.3093 | 37.2037 | 40.9719 | -0.8059 | 18.519 |
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+ | 1.084 | 16.0 | 4272 | 1.1146 | 42.9053 | 23.2391 | 37.0542 | 40.8826 | -0.8104 | 18.533 |
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+ | 1.0755 | 17.0 | 4539 | 1.1124 | 43.0429 | 23.2773 | 37.1389 | 41.0755 | -0.8086 | 18.544 |
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+ | 1.0748 | 18.0 | 4806 | 1.1121 | 43.2243 | 23.4179 | 37.2039 | 41.143 | -0.8048 | 18.548 |
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+ | 1.072 | 19.0 | 5073 | 1.1106 | 43.1776 | 23.3061 | 37.3105 | 41.1392 | -0.8039 | 18.549 |
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+ | 1.0671 | 20.0 | 5340 | 1.1108 | 43.1145 | 23.2262 | 37.218 | 41.0897 | -0.8051 | 18.549 |
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  ### Framework versions