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bart-large-cnn-finetuned-scope-summarization

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  1. README.md +25 -25
  2. model.safetensors +1 -1
  3. runs/Mar03_09-14-02_nnlg1me7ob/events.out.tfevents.1709457247.nnlg1me7ob.368.0 +2 -2
  4. runs/Mar03_09-14-02_nnlg1me7ob/events.out.tfevents.1709459964.nnlg1me7ob.368.1 +3 -0
README.md CHANGED
@@ -17,11 +17,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0576
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- - Rouge1: 72.4845
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- - Rouge2: 56.2823
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- - Rougel: 63.4557
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- - Rougelsum: 63.5967
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  ## Model description
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@@ -52,26 +52,26 @@ 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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- | 0.9015 | 1.0 | 43 | 0.6314 | 51.6991 | 31.3961 | 38.9086 | 39.0216 |
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- | 0.6229 | 2.0 | 86 | 0.5361 | 44.8657 | 26.0694 | 35.6835 | 35.5961 |
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- | 0.5471 | 3.0 | 129 | 0.4637 | 58.1901 | 39.1067 | 44.6125 | 44.6485 |
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- | 0.4933 | 4.0 | 172 | 0.4317 | 59.2043 | 38.8231 | 42.3279 | 42.3126 |
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- | 0.4483 | 5.0 | 215 | 0.3785 | 58.613 | 38.2681 | 44.9075 | 44.9251 |
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- | 0.4044 | 6.0 | 258 | 0.3355 | 59.6825 | 40.0687 | 45.4193 | 45.4072 |
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- | 0.3622 | 7.0 | 301 | 0.2931 | 62.1522 | 42.1594 | 46.7405 | 46.6808 |
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- | 0.3157 | 8.0 | 344 | 0.2802 | 58.9892 | 40.1726 | 45.8148 | 45.6941 |
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- | 0.2657 | 9.0 | 387 | 0.2011 | 67.0955 | 48.3435 | 54.1678 | 54.239 |
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- | 0.2135 | 10.0 | 430 | 0.1626 | 65.9099 | 47.3273 | 51.3779 | 51.4268 |
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- | 0.1674 | 11.0 | 473 | 0.1357 | 65.2031 | 46.9953 | 53.0477 | 53.0226 |
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- | 0.1263 | 12.0 | 516 | 0.1025 | 66.5646 | 48.6747 | 53.8395 | 53.8693 |
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- | 0.0934 | 13.0 | 559 | 0.0964 | 67.734 | 51.1863 | 57.4624 | 57.5316 |
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- | 0.0721 | 14.0 | 602 | 0.0738 | 70.5697 | 53.1366 | 59.5014 | 59.6962 |
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- | 0.0524 | 15.0 | 645 | 0.0664 | 70.7311 | 55.0735 | 61.6224 | 61.6253 |
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- | 0.042 | 16.0 | 688 | 0.0459 | 72.6542 | 56.8195 | 62.0931 | 62.1472 |
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- | 0.0325 | 17.0 | 731 | 0.0535 | 69.6733 | 52.693 | 59.3506 | 59.2689 |
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- | 0.0248 | 18.0 | 774 | 0.0510 | 71.5589 | 55.3445 | 62.3074 | 62.1671 |
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- | 0.0195 | 19.0 | 817 | 0.0552 | 71.0699 | 54.6459 | 63.1885 | 63.1925 |
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- | 0.0164 | 20.0 | 860 | 0.0576 | 72.4845 | 56.2823 | 63.4557 | 63.5967 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0570
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+ - Rouge1: 73.0523
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+ - Rouge2: 57.189
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+ - Rougel: 63.7863
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+ - Rougelsum: 63.6277
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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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+ | 0.9009 | 1.0 | 43 | 0.7132 | 37.6307 | 19.9878 | 28.3308 | 28.3651 |
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+ | 0.6239 | 2.0 | 86 | 0.6394 | 39.1948 | 21.1172 | 29.1431 | 29.2046 |
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+ | 0.5428 | 3.0 | 129 | 0.5885 | 57.4199 | 37.8978 | 43.0583 | 43.0034 |
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+ | 0.4857 | 4.0 | 172 | 0.5204 | 57.0063 | 36.0008 | 43.8824 | 43.6754 |
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+ | 0.4436 | 5.0 | 215 | 0.4770 | 60.0159 | 41.1676 | 45.8763 | 45.767 |
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+ | 0.3918 | 6.0 | 258 | 0.4266 | 62.6838 | 43.0127 | 48.1281 | 47.8622 |
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+ | 0.3526 | 7.0 | 301 | 0.3420 | 63.2047 | 44.3474 | 49.3164 | 49.1797 |
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+ | 0.3138 | 8.0 | 344 | 0.3241 | 63.0339 | 43.0567 | 48.2804 | 48.2779 |
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+ | 0.2655 | 9.0 | 387 | 0.2640 | 66.8968 | 47.6739 | 54.0001 | 53.9609 |
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+ | 0.2215 | 10.0 | 430 | 0.2101 | 66.4286 | 48.4482 | 54.3566 | 54.5065 |
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+ | 0.1707 | 11.0 | 473 | 0.1497 | 67.4439 | 50.1131 | 57.1864 | 57.168 |
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+ | 0.1351 | 12.0 | 516 | 0.1275 | 70.2057 | 53.5349 | 59.2034 | 59.207 |
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+ | 0.1033 | 13.0 | 559 | 0.1161 | 70.6876 | 52.8255 | 59.3882 | 59.1475 |
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+ | 0.0764 | 14.0 | 602 | 0.0798 | 71.8239 | 54.9631 | 61.0645 | 60.7883 |
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+ | 0.0544 | 15.0 | 645 | 0.0784 | 73.1602 | 56.4301 | 62.3908 | 62.4026 |
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+ | 0.0433 | 16.0 | 688 | 0.0627 | 71.4275 | 55.8176 | 61.6217 | 61.6363 |
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+ | 0.0313 | 17.0 | 731 | 0.0573 | 73.1143 | 57.4068 | 65.0764 | 64.9105 |
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+ | 0.0248 | 18.0 | 774 | 0.0583 | 73.2775 | 57.1978 | 64.5147 | 64.5203 |
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+ | 0.0188 | 19.0 | 817 | 0.0600 | 74.0462 | 59.1939 | 65.6102 | 65.4091 |
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+ | 0.0166 | 20.0 | 860 | 0.0570 | 73.0523 | 57.189 | 63.7863 | 63.6277 |
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  ### Framework versions
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