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BERT2BERT_finetuned

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update model card README.md

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@@ -15,11 +15,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [JulienRPA/BERT2BERT_pretrained_LC-QuAD_2.0](https://huggingface.co/JulienRPA/BERT2BERT_pretrained_LC-QuAD_2.0) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3523
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- - Bleu: 95.2821
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- - Em: 0.1415
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- - Rm: 0.3046
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- - Gen Len: 58.7746
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  ## Model description
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@@ -51,29 +51,29 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Bleu | Em | Gen Len | Validation Loss | Rm |
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  |:-------------:|:------:|:-----:|:-------:|:------:|:-------:|:---------------:|:------:|
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- | 4.0279 | 12.82 | 500 | 49.841 | 0.0 | 51.6403 | 2.4031 | 0.0 |
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- | 1.3442 | 25.64 | 1000 | 85.0177 | 0.0 | 57.9784 | 0.5014 | 0.0 |
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- | 0.2522 | 38.46 | 1500 | 94.0714 | 0.0168 | 57.9137 | 0.3293 | 0.0216 |
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- | 0.1534 | 51.28 | 2000 | 94.4328 | 0.0024 | 58.9448 | 0.3207 | 0.0072 |
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- | 0.1305 | 64.1 | 2500 | 94.0708 | 0.0 | 59.6115 | 0.3247 | 0.0 |
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- | 0.1226 | 76.92 | 3000 | 94.3143 | 0.0024 | 58.235 | 0.3325 | 0.0024 |
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- | 0.1131 | 89.74 | 3500 | 94.5678 | 0.0048 | 59.6811 | 0.3401 | 0.0144 |
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- | 0.1053 | 102.56 | 4000 | 94.4738 | 0.0168 | 59.0288 | 0.3374 | 0.0552 |
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- | 0.0999 | 115.38 | 4500 | 94.6291 | 0.0336 | 58.6283 | 0.3437 | 0.0624 |
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- | 0.0941 | 128.21 | 5000 | 94.7896 | 0.0695 | 58.4149 | 0.3512 | 0.1271 |
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- | 0.0904 | 141.03 | 5500 | 94.4101 | 0.0719 | 58.2518 | 0.3424 | 0.1439 |
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- | 0.0833 | 153.85 | 6000 | 94.7141 | 0.0887 | 59.0312 | 0.3462 | 0.1775 |
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- | 0.0772 | 166.67 | 6500 | 94.6758 | 0.0911 | 59.0767 | 0.3467 | 0.2062 |
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- | 0.0722 | 179.49 | 7000 | 94.5698 | 0.1055 | 58.1415 | 0.3462 | 0.2398 |
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- | 0.0669 | 192.31 | 7500 | 95.0365 | 0.1223 | 58.7794 | 0.3537 | 0.2782 |
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- | 0.062 | 205.13 | 8000 | 94.8694 | 0.1247 | 58.211 | 0.3505 | 0.2686 |
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- | 0.0576 | 217.95 | 8500 | 94.8168 | 0.1271 | 59.0791 | 0.3511 | 0.2926 |
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- | 0.0539 | 230.77 | 9000 | 95.1935 | 0.1367 | 58.6787 | 0.3490 | 0.3046 |
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- | 0.0502 | 243.59 | 9500 | 95.1882 | 0.1319 | 58.5228 | 0.3490 | 0.3141 |
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- | 0.0473 | 256.41 | 10000 | 95.1198 | 0.1319 | 58.4245 | 0.3504 | 0.307 |
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- | 0.045 | 269.23 | 10500 | 0.3505 | 95.047 | 0.1343 | 0.307 | 58.3213|
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- | 0.0429 | 282.05 | 11000 | 0.3522 | 95.2397| 0.1391 | 0.3046 | 58.7242|
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- | 0.0416 | 294.87 | 11500 | 0.3523 | 95.2821| 0.1415 | 0.3046 | 58.7746|
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  ### Framework versions
 
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  This model is a fine-tuned version of [JulienRPA/BERT2BERT_pretrained_LC-QuAD_2.0](https://huggingface.co/JulienRPA/BERT2BERT_pretrained_LC-QuAD_2.0) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1672
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+ - Bleu: 96.7679
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+ - Em: 0.6307
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+ - Rm: 0.7482
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+ - Gen Len: 75.6355
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  ## Model description
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  | Training Loss | Epoch | Step | Bleu | Em | Gen Len | Validation Loss | Rm |
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  |:-------------:|:------:|:-----:|:-------:|:------:|:-------:|:---------------:|:------:|
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+ | 3.4354 | 12.82 | 500 | 56.6427 | 0.0 | 70.5947 | 1.5065 | 0.0 |
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+ | 0.8473 | 25.64 | 1000 | 90.5419 | 0.0192 | 76.9736 | 0.3859 | 0.0216 |
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+ | 0.2049 | 38.46 | 1500 | 93.6495 | 0.0504 | 75.1655 | 0.2472 | 0.0671 |
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+ | 0.1222 | 51.28 | 2000 | 93.8388 | 0.0959 | 75.6403 | 0.2338 | 0.1487 |
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+ | 0.0923 | 64.1 | 2500 | 94.71 | 0.2158 | 75.8177 | 0.1944 | 0.2662 |
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+ | 0.0752 | 76.92 | 3000 | 95.0458 | 0.2662 | 75.2638 | 0.1990 | 0.3022 |
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+ | 0.0627 | 89.74 | 3500 | 95.3518 | 0.3429 | 76.9928 | 0.1957 | 0.3957 |
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+ | 0.052 | 102.56 | 4000 | 95.5392 | 0.3837 | 76.1007 | 0.1861 | 0.4508 |
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+ | 0.0457 | 115.38 | 4500 | 95.6692 | 0.4173 | 76.1727 | 0.1880 | 0.4892 |
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+ | 0.0386 | 128.21 | 5000 | 95.9215 | 0.446 | 76.0168 | 0.1850 | 0.5276 |
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+ | 0.0321 | 141.03 | 5500 | 95.931 | 0.4964 | 75.2566 | 0.1724 | 0.5875 |
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+ | 0.026 | 153.85 | 6000 | 96.4317 | 0.5348 | 75.741 | 0.1687 | 0.6499 |
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+ | 0.0242 | 166.67 | 6500 | 96.197 | 0.5372 | 76.1127 | 0.1707 | 0.6403 |
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+ | 0.0193 | 179.49 | 7000 | 96.3422 | 0.5564 | 75.3933 | 0.1643 | 0.6691 |
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+ | 0.0164 | 192.31 | 7500 | 96.5278 | 0.5779 | 75.4508 | 0.1650 | 0.693 |
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+ | 0.0139 | 205.13 | 8000 | 96.6382 | 0.6091 | 75.9592 | 0.1668 | 0.7314 |
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+ | 0.012 | 217.95 | 8500 | 96.5488 | 0.6163 | 76.0024 | 0.1644 | 0.729 |
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+ | 0.0106 | 230.77 | 9000 | 96.6353 | 0.6091 | 75.5468 | 0.1653 | 0.7266 |
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+ | 0.0093 | 243.59 | 9500 | 96.8984 | 0.6331 | 75.7242 | 0.1663 | 0.7482 |
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+ | 0.0084 | 256.41 | 10000 | 96.6199 | 0.6331 | 75.3885 | 0.1676 | 0.7482 |
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+ | 0.0076 | 269.23 | 10500 | 0.1678 | 96.5038| 0.6283 | 0.7482 | 75.3453|
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+ | 0.007 | 282.05 | 11000 | 0.1669 | 96.7187| 0.6355 | 0.7458 | 75.9281|
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+ | 0.0065 | 294.87 | 11500 | 0.1672 | 96.7679| 0.6307 | 0.7482 | 75.6355|
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  ### Framework versions