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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_02-42-27_n40yshtgh3/events.out.tfevents.1709433753.n40yshtgh3.990.0 +2 -2
  4. runs/Mar03_02-42-27_n40yshtgh3/events.out.tfevents.1709436876.n40yshtgh3.990.1 +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: 0.0440
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- - Rouge1: 71.9228
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- - Rouge2: 55.9885
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- - Rougel: 63.9261
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- - Rougelsum: 63.9399
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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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- | 0.9018 | 1.0 | 43 | 0.6756 | 50.3755 | 30.7155 | 38.6179 | 38.6264 |
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- | 0.6245 | 2.0 | 86 | 0.5850 | 51.4445 | 31.9585 | 39.4968 | 39.5228 |
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- | 0.5542 | 3.0 | 129 | 0.4953 | 57.8006 | 38.5407 | 44.1007 | 44.1212 |
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- | 0.4924 | 4.0 | 172 | 0.4465 | 59.3159 | 39.8881 | 44.3422 | 44.4364 |
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- | 0.4471 | 5.0 | 215 | 0.4068 | 60.2098 | 41.0154 | 46.7304 | 46.8042 |
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- | 0.4022 | 6.0 | 258 | 0.3936 | 63.0134 | 43.8191 | 47.7963 | 47.7634 |
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- | 0.3591 | 7.0 | 301 | 0.3147 | 60.7072 | 41.4999 | 47.0323 | 46.9748 |
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- | 0.3147 | 8.0 | 344 | 0.2828 | 63.5097 | 44.1285 | 50.2938 | 50.3711 |
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- | 0.2675 | 9.0 | 387 | 0.2310 | 65.7933 | 48.403 | 53.5596 | 53.644 |
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- | 0.2128 | 10.0 | 430 | 0.1637 | 65.7322 | 47.6943 | 53.5761 | 53.4632 |
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- | 0.1631 | 11.0 | 473 | 0.1270 | 68.0034 | 49.3799 | 56.526 | 56.604 |
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- | 0.1252 | 12.0 | 516 | 0.0753 | 67.5687 | 49.2524 | 54.2558 | 54.3242 |
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- | 0.0928 | 13.0 | 559 | 0.0909 | 70.9444 | 54.1944 | 60.1015 | 60.1451 |
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- | 0.0686 | 14.0 | 602 | 0.0673 | 71.0886 | 54.3136 | 61.369 | 61.235 |
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- | 0.0522 | 15.0 | 645 | 0.0627 | 71.1362 | 53.5389 | 60.8795 | 60.9924 |
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- | 0.0398 | 16.0 | 688 | 0.0463 | 68.818 | 51.7116 | 58.7056 | 58.7268 |
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- | 0.0321 | 17.0 | 731 | 0.0397 | 73.1967 | 57.5225 | 65.6753 | 65.6779 |
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- | 0.0249 | 18.0 | 774 | 0.0436 | 73.2201 | 56.8754 | 65.0215 | 65.0161 |
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- | 0.0189 | 19.0 | 817 | 0.0446 | 73.9096 | 58.3484 | 65.6389 | 65.6056 |
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- | 0.0155 | 20.0 | 860 | 0.0440 | 71.9228 | 55.9885 | 63.9261 | 63.9399 |
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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: 0.0576
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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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  | 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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