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flan-t5-base

Text2Text Generation
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t5
simplification
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@@ -5,16 +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: flan-t5-base-clara-med
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  results: []
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- datasets:
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- - lcampillos/CLARA-MeD
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- dataset:
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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
@@ -22,14 +15,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # flan-t5-base-clara-med
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- This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) 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: 1.2296
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- - Rouge1: 29.9558
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- - Rouge2: 16.9558
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- - Rougel: 28.1645
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- - Rougelsum: 28.1582
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- - SARI: 42.3045
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  ## Model description
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@@ -60,36 +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 | 380 | 1.4310 | 27.8189 | 15.801 | 26.3299 | 26.2963 |
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- | No log | 2.0 | 760 | 1.3600 | 28.154 | 15.998 | 26.6032 | 26.606 |
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- | 1.6592 | 3.0 | 1140 | 1.3062 | 28.5836 | 16.3289 | 27.1685 | 27.1789 |
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- | 1.6592 | 4.0 | 1520 | 1.2747 | 29.1122 | 16.6792 | 27.5758 | 27.5733 |
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- | 1.3824 | 5.0 | 1900 | 1.2505 | 28.9849 | 16.4234 | 27.343 | 27.3457 |
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- | 1.3824 | 6.0 | 2280 | 1.2358 | 29.2208 | 16.7068 | 27.5005 | 27.4958 |
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- | 1.3824 | 7.0 | 2660 | 1.2317 | 29.4609 | 17.1435 | 27.7924 | 27.809 |
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- | 1.2296 | 8.0 | 3040 | 1.2215 | 29.9464 | 17.1933 | 28.1208 | 28.1532 |
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- | 1.2296 | 9.0 | 3420 | 1.2187 | 29.8723 | 17.2898 | 27.9957 | 28.0209 |
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- | 1.1295 | 10.0 | 3800 | 1.2143 | 29.76 | 17.2644 | 27.9598 | 27.9482 |
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- | 1.1295 | 11.0 | 4180 | 1.2044 | 29.5394 | 16.9554 | 27.7543 | 27.7495 |
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- | 1.1295 | 12.0 | 4560 | 1.2082 | 29.6155 | 17.0565 | 27.9131 | 27.9027 |
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- | 1.0493 | 13.0 | 4940 | 1.2047 | 30.0647 | 17.314 | 28.3498 | 28.3241 |
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- | 1.0493 | 14.0 | 5320 | 1.2073 | 29.8209 | 17.0308 | 27.9766 | 27.9716 |
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- | 0.9857 | 15.0 | 5700 | 1.2058 | 29.7392 | 17.0373 | 28.0291 | 28.029 |
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- | 0.9857 | 16.0 | 6080 | 1.2077 | 30.1819 | 17.298 | 28.3771 | 28.3706 |
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- | 0.9857 | 17.0 | 6460 | 1.2043 | 30.0708 | 17.2588 | 28.3525 | 28.3654 |
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- | 0.9331 | 18.0 | 6840 | 1.2103 | 29.9749 | 17.0748 | 28.1575 | 28.1827 |
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- | 0.9331 | 19.0 | 7220 | 1.2086 | 29.561 | 16.8513 | 27.7646 | 27.7808 |
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- | 0.8997 | 20.0 | 7600 | 1.2183 | 30.1109 | 17.186 | 28.3103 | 28.3078 |
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- | 0.8997 | 21.0 | 7980 | 1.2177 | 29.851 | 17.0093 | 28.0336 | 28.0348 |
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- | 0.8997 | 22.0 | 8360 | 1.2181 | 30.2841 | 17.5662 | 28.5167 | 28.526 |
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- | 0.8628 | 23.0 | 8740 | 1.2224 | 29.8959 | 17.0802 | 28.1386 | 28.1456 |
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- | 0.8628 | 24.0 | 9120 | 1.2244 | 29.9 | 17.1425 | 28.1456 | 28.1179 |
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- | 0.8369 | 25.0 | 9500 | 1.2234 | 30.0394 | 17.0066 | 28.2387 | 28.2345 |
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- | 0.8369 | 26.0 | 9880 | 1.2266 | 29.9758 | 17.1042 | 28.2635 | 28.2669 |
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- | 0.8369 | 27.0 | 10260 | 1.2263 | 29.893 | 16.993 | 28.0106 | 28.0009 |
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- | 0.8187 | 28.0 | 10640 | 1.2272 | 29.9718 | 17.0048 | 28.1821 | 28.1751 |
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- | 0.8187 | 29.0 | 11020 | 1.2279 | 29.973 | 17.0096 | 28.1837 | 28.1655 |
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- | 0.8181 | 30.0 | 11400 | 1.2296 | 29.9558 | 16.9558 | 28.1645 | 28.1582 |
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  ### Framework versions
@@ -97,4 +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: flan-t5-base-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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  # flan-t5-base-clara-med
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+ This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2682
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+ - Rouge1: 28.7943
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+ - Rouge2: 16.031
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+ - Rougel: 26.7637
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+ - Rougelsum: 26.8047
 
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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 | 380 | 1.4589 | 27.2058 | 14.9978 | 25.5534 | 25.5731 |
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+ | No log | 2.0 | 760 | 1.3896 | 27.2408 | 14.7703 | 25.4948 | 25.5166 |
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+ | 1.6471 | 3.0 | 1140 | 1.3369 | 27.4133 | 14.8527 | 25.6991 | 25.6951 |
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+ | 1.6471 | 4.0 | 1520 | 1.3050 | 27.8128 | 15.1101 | 26.1084 | 26.1375 |
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+ | 1.3668 | 5.0 | 1900 | 1.2909 | 27.8076 | 15.3018 | 26.0053 | 26.0502 |
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+ | 1.3668 | 6.0 | 2280 | 1.2732 | 27.9007 | 15.2226 | 26.0983 | 26.1265 |
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+ | 1.3668 | 7.0 | 2660 | 1.2600 | 27.5606 | 14.8875 | 25.6058 | 25.6407 |
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+ | 1.2209 | 8.0 | 3040 | 1.2499 | 28.0251 | 15.3935 | 26.1269 | 26.1526 |
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+ | 1.2209 | 9.0 | 3420 | 1.2510 | 28.2472 | 15.5229 | 26.2721 | 26.2975 |
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+ | 1.1212 | 10.0 | 3800 | 1.2485 | 28.2394 | 15.4929 | 26.2322 | 26.2664 |
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+ | 1.1212 | 11.0 | 4180 | 1.2380 | 28.3943 | 15.4261 | 26.4591 | 26.5035 |
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+ | 1.1212 | 12.0 | 4560 | 1.2373 | 28.3341 | 15.5314 | 26.4204 | 26.4567 |
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+ | 1.0353 | 13.0 | 4940 | 1.2392 | 28.3379 | 15.7147 | 26.4372 | 26.4395 |
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+ | 1.0353 | 14.0 | 5320 | 1.2436 | 28.6789 | 15.7709 | 26.5923 | 26.6221 |
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+ | 0.9837 | 15.0 | 5700 | 1.2447 | 28.801 | 15.9612 | 26.7568 | 26.7808 |
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+ | 0.9837 | 16.0 | 6080 | 1.2406 | 28.3076 | 15.5614 | 26.3192 | 26.3439 |
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+ | 0.9837 | 17.0 | 6460 | 1.2450 | 28.4635 | 15.8162 | 26.5962 | 26.6047 |
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+ | 0.9314 | 18.0 | 6840 | 1.2481 | 28.3993 | 15.63 | 26.3544 | 26.4098 |
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+ | 0.9314 | 19.0 | 7220 | 1.2505 | 28.4367 | 15.8777 | 26.4985 | 26.5426 |
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+ | 0.8877 | 20.0 | 7600 | 1.2536 | 28.5426 | 15.7746 | 26.5987 | 26.6552 |
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+ | 0.8877 | 21.0 | 7980 | 1.2524 | 28.8175 | 16.1677 | 26.8577 | 26.9171 |
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+ | 0.8877 | 22.0 | 8360 | 1.2604 | 28.5719 | 15.9639 | 26.632 | 26.659 |
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+ | 0.8577 | 23.0 | 8740 | 1.2591 | 28.7079 | 15.878 | 26.7358 | 26.7978 |
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+ | 0.8577 | 24.0 | 9120 | 1.2606 | 28.6595 | 15.9726 | 26.6673 | 26.7347 |
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+ | 0.8337 | 25.0 | 9500 | 1.2686 | 28.6858 | 15.9056 | 26.6485 | 26.6785 |
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+ | 0.8337 | 26.0 | 9880 | 1.2654 | 28.6585 | 16.0482 | 26.688 | 26.7329 |
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+ | 0.8337 | 27.0 | 10260 | 1.2618 | 28.7773 | 15.9875 | 26.6868 | 26.7367 |
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+ | 0.8163 | 28.0 | 10640 | 1.2668 | 28.7499 | 16.0041 | 26.7845 | 26.8112 |
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+ | 0.8163 | 29.0 | 11020 | 1.2671 | 28.7373 | 15.9702 | 26.7276 | 26.763 |
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+ | 0.8087 | 30.0 | 11400 | 1.2682 | 28.7943 | 16.031 | 26.7637 | 26.8047 |
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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