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training completed[prod]:pegasus-extractive-500

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README.md CHANGED
@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0569
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  ## Model description
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@@ -46,28 +46,28 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 0.09 | 250 | 4.5676 |
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- | 4.9309 | 0.18 | 500 | 4.1409 |
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- | 4.9309 | 0.27 | 750 | 1.9459 |
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- | 2.7387 | 0.35 | 1000 | 1.1953 |
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- | 2.7387 | 0.44 | 1250 | 1.1557 |
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- | 1.3603 | 0.53 | 1500 | 1.1350 |
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- | 1.3603 | 0.62 | 1750 | 1.1189 |
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- | 1.2237 | 0.71 | 2000 | 1.1092 |
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- | 1.2237 | 0.8 | 2250 | 1.0976 |
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- | 1.2113 | 0.89 | 2500 | 1.0931 |
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- | 1.2113 | 0.98 | 2750 | 1.0854 |
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- | 1.2057 | 1.06 | 3000 | 1.0787 |
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- | 1.2057 | 1.15 | 3250 | 1.0759 |
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- | 1.1613 | 1.24 | 3500 | 1.0714 |
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- | 1.1613 | 1.33 | 3750 | 1.0680 |
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- | 1.1379 | 1.42 | 4000 | 1.0662 |
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- | 1.1379 | 1.51 | 4250 | 1.0634 |
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- | 1.163 | 1.6 | 4500 | 1.0622 |
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- | 1.163 | 1.68 | 4750 | 1.0600 |
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- | 1.1271 | 1.77 | 5000 | 1.0587 |
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- | 1.1271 | 1.86 | 5250 | 1.0574 |
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- | 1.1358 | 1.95 | 5500 | 1.0569 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1536
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 0.09 | 250 | 4.6880 |
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+ | 5.0042 | 0.18 | 500 | 4.2185 |
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+ | 5.0042 | 0.27 | 750 | 1.6267 |
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+ | 2.6655 | 0.35 | 1000 | 1.2804 |
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+ | 2.6655 | 0.44 | 1250 | 1.2502 |
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+ | 1.4309 | 0.53 | 1500 | 1.2319 |
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+ | 1.4309 | 0.62 | 1750 | 1.2174 |
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+ | 1.3166 | 0.71 | 2000 | 1.2072 |
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+ | 1.3166 | 0.8 | 2250 | 1.1978 |
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+ | 1.2982 | 0.89 | 2500 | 1.1904 |
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+ | 1.2982 | 0.98 | 2750 | 1.1829 |
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+ | 1.3028 | 1.06 | 3000 | 1.1765 |
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+ | 1.3028 | 1.15 | 3250 | 1.1727 |
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+ | 1.2443 | 1.24 | 3500 | 1.1685 |
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+ | 1.2443 | 1.33 | 3750 | 1.1652 |
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+ | 1.2306 | 1.42 | 4000 | 1.1632 |
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+ | 1.2306 | 1.51 | 4250 | 1.1600 |
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+ | 1.2533 | 1.6 | 4500 | 1.1586 |
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+ | 1.2533 | 1.68 | 4750 | 1.1562 |
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+ | 1.2127 | 1.77 | 5000 | 1.1550 |
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+ | 1.2127 | 1.86 | 5250 | 1.1544 |
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+ | 1.2235 | 1.95 | 5500 | 1.1536 |
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  ### Framework versions
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