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mbart-large-50

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@@ -5,14 +5,9 @@ tags:
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  - generated_from_trainer
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  metrics:
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  - rouge
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- - sari
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  model-index:
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  - name: mbart-large-50-clara-med
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  results: []
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- datasets:
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- - lcampillos/CLARA-MeD
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- language:
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- - es
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -20,14 +15,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # mbart-large-50-clara-med
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- This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the [CLARA-MeD](https://huggingface.co/lcampillos/CLARA-MeD) dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.0952
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- - Rouge1: 49.4298
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- - Rouge2: 31.7193
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- - Rougel: 44.732
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- - Rougelsum: 44.9281
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- - SARI: 51.3461
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  ## Model description
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@@ -58,36 +52,36 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
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- | No log | 1.0 | 190 | 9.5151 | 8.9002 | 0.0056 | 8.9059 | 8.8991 |
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- | No log | 2.0 | 380 | 1.7786 | 44.8765 | 27.9652 | 40.2081 | 40.3457 |
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- | 4.488 | 3.0 | 570 | 1.7104 | 46.4054 | 28.8582 | 41.6579 | 41.86 |
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- | 4.488 | 4.0 | 760 | 1.7601 | 47.6046 | 30.1854 | 42.9171 | 43.0745 |
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- | 1.1057 | 5.0 | 950 | 1.9232 | 48.1693 | 30.1535 | 43.0418 | 43.1796 |
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- | 1.1057 | 6.0 | 1140 | 2.2791 | 43.831 | 26.9216 | 39.1768 | 39.3672 |
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- | 1.1057 | 7.0 | 1330 | 2.4800 | 42.4614 | 25.2371 | 37.6735 | 37.9309 |
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- | 0.4401 | 8.0 | 1520 | 2.4991 | 46.6653 | 28.9836 | 42.1188 | 42.2492 |
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- | 0.4401 | 9.0 | 1710 | 2.5826 | 47.2784 | 29.8703 | 42.622 | 42.7514 |
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- | 0.2523 | 10.0 | 1900 | 2.6356 | 48.0382 | 30.8884 | 43.3523 | 43.5068 |
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- | 0.2523 | 11.0 | 2090 | 2.6141 | 47.6911 | 29.3254 | 42.4938 | 42.6519 |
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- | 0.2523 | 12.0 | 2280 | 2.6942 | 48.7597 | 30.9279 | 43.5391 | 43.6974 |
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- | 0.1613 | 13.0 | 2470 | 2.7194 | 49.0916 | 30.9767 | 43.9943 | 44.1572 |
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- | 0.1613 | 14.0 | 2660 | 2.7911 | 47.8223 | 30.6173 | 43.1809 | 43.3471 |
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- | 0.1305 | 15.0 | 2850 | 2.8370 | 47.5629 | 29.7783 | 42.7168 | 42.8503 |
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- | 0.1305 | 16.0 | 3040 | 2.8588 | 49.4762 | 31.6101 | 44.5422 | 44.7027 |
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- | 0.1305 | 17.0 | 3230 | 2.9082 | 49.1502 | 31.4654 | 44.2166 | 44.3186 |
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- | 0.141 | 18.0 | 3420 | 2.8887 | 48.9675 | 31.0485 | 44.177 | 44.3258 |
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- | 0.141 | 19.0 | 3610 | 2.9043 | 49.2936 | 31.5204 | 44.2215 | 44.4216 |
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- | 0.1096 | 20.0 | 3800 | 2.9549 | 48.0316 | 30.4505 | 42.9444 | 43.0893 |
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- | 0.1096 | 21.0 | 3990 | 2.9666 | 49.2276 | 31.2755 | 44.2435 | 44.4591 |
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- | 0.1096 | 22.0 | 4180 | 2.9697 | 49.1008 | 31.4931 | 44.1893 | 44.382 |
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- | 0.0773 | 23.0 | 4370 | 2.9970 | 49.3707 | 31.4672 | 44.6066 | 44.7685 |
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- | 0.0773 | 24.0 | 4560 | 3.0081 | 49.2172 | 31.4693 | 44.4235 | 44.5458 |
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- | 0.048 | 25.0 | 4750 | 2.9968 | 49.4847 | 31.8341 | 44.8464 | 45.0286 |
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- | 0.048 | 26.0 | 4940 | 3.0405 | 49.5724 | 31.612 | 44.5192 | 44.7717 |
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- | 0.048 | 27.0 | 5130 | 3.0651 | 49.0194 | 31.2473 | 44.177 | 44.3837 |
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- | 0.0274 | 28.0 | 5320 | 3.0740 | 49.2999 | 31.5672 | 44.56 | 44.8105 |
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- | 0.0274 | 29.0 | 5510 | 3.0842 | 49.2898 | 31.602 | 44.5414 | 44.754 |
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- | 0.0168 | 30.0 | 5700 | 3.0952 | 49.4298 | 31.7193 | 44.732 | 44.9281 |
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  ### Framework versions
@@ -95,4 +89,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.25.1
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  - Pytorch 1.13.0
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  - Datasets 2.8.0
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- - Tokenizers 0.12.1
 
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  - generated_from_trainer
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  metrics:
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  - rouge
 
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  model-index:
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  - name: mbart-large-50-clara-med
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  results: []
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # mbart-large-50-clara-med
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+ This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.2175
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+ - Rouge1: 48.3311
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+ - Rouge2: 30.5638
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+ - Rougel: 43.5214
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+ - Rougelsum: 43.6488
 
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
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+ | No log | 1.0 | 190 | 3.2394 | 16.8539 | 2.7013 | 12.425 | 12.5286 |
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+ | No log | 2.0 | 380 | 1.7381 | 44.5316 | 27.8022 | 40.1591 | 40.3177 |
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+ | 3.4249 | 3.0 | 570 | 1.7198 | 45.6463 | 28.6925 | 41.263 | 41.4703 |
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+ | 3.4249 | 4.0 | 760 | 1.9450 | 43.0233 | 26.3397 | 38.7518 | 38.9154 |
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+ | 0.8377 | 5.0 | 950 | 2.1068 | 46.5936 | 28.7218 | 41.7184 | 41.8448 |
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+ | 0.8377 | 6.0 | 1140 | 2.2815 | 46.4517 | 28.5639 | 41.8107 | 41.9996 |
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+ | 0.8377 | 7.0 | 1330 | 2.4726 | 46.0403 | 28.1887 | 40.9183 | 41.0318 |
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+ | 0.3195 | 8.0 | 1520 | 2.5690 | 47.255 | 29.1482 | 42.4463 | 42.5728 |
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+ | 0.3195 | 9.0 | 1710 | 2.6753 | 46.5967 | 28.5688 | 41.414 | 41.5889 |
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+ | 0.1925 | 10.0 | 1900 | 2.7276 | 46.3251 | 28.4889 | 41.4556 | 41.581 |
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+ | 0.1925 | 11.0 | 2090 | 2.7638 | 46.9325 | 29.2558 | 41.726 | 41.8413 |
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+ | 0.1925 | 12.0 | 2280 | 2.8273 | 47.0344 | 29.1298 | 41.7291 | 41.9236 |
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+ | 0.1313 | 13.0 | 2470 | 2.8633 | 47.5234 | 29.6376 | 42.3409 | 42.4372 |
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+ | 0.1313 | 14.0 | 2660 | 2.8989 | 47.0396 | 29.117 | 41.9893 | 42.1846 |
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+ | 0.1117 | 15.0 | 2850 | 2.9691 | 47.8406 | 29.889 | 42.5645 | 42.7676 |
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+ | 0.1117 | 16.0 | 3040 | 2.9763 | 46.9489 | 28.9919 | 41.8404 | 42.0141 |
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+ | 0.1117 | 17.0 | 3230 | 2.9985 | 47.6628 | 29.7341 | 42.6382 | 42.7649 |
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+ | 0.0824 | 18.0 | 3420 | 3.0511 | 48.0627 | 30.4108 | 43.1693 | 43.3489 |
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+ | 0.0824 | 19.0 | 3610 | 3.0102 | 48.05 | 29.9552 | 43.1462 | 43.3421 |
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+ | 0.0467 | 20.0 | 3800 | 3.0520 | 47.5451 | 29.6129 | 42.6499 | 42.7968 |
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+ | 0.0467 | 21.0 | 3990 | 3.0978 | 47.5042 | 29.6191 | 42.6093 | 42.7341 |
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+ | 0.0467 | 22.0 | 4180 | 3.1270 | 47.8301 | 29.9484 | 42.6866 | 42.9179 |
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+ | 0.0246 | 23.0 | 4370 | 3.1435 | 47.6683 | 30.1974 | 43.0456 | 43.1496 |
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+ | 0.0246 | 24.0 | 4560 | 3.1599 | 47.8652 | 30.2751 | 43.0445 | 43.1898 |
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+ | 0.013 | 25.0 | 4750 | 3.1750 | 48.1352 | 30.4185 | 43.0485 | 43.2456 |
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+ | 0.013 | 26.0 | 4940 | 3.1939 | 47.9653 | 30.3968 | 43.1271 | 43.2522 |
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+ | 0.013 | 27.0 | 5130 | 3.2054 | 48.2122 | 30.6 | 43.3461 | 43.4629 |
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+ | 0.0071 | 28.0 | 5320 | 3.1964 | 47.924 | 30.3089 | 43.0402 | 43.2016 |
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+ | 0.0071 | 29.0 | 5510 | 3.2123 | 48.2967 | 30.5088 | 43.431 | 43.5384 |
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+ | 0.005 | 30.0 | 5700 | 3.2175 | 48.3311 | 30.5638 | 43.5214 | 43.6488 |
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  ### Framework versions
 
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  - Transformers 4.25.1
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  - Pytorch 1.13.0
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  - Datasets 2.8.0
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+ - Tokenizers 0.12.1