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bart-large-cnn-finetuned-scope-summarization-train-test-split

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  1. README.md +27 -27
  2. generation_config.json +1 -1
  3. model.safetensors +1 -1
  4. runs/Mar02_17-15-34_n5qclzvvia/events.out.tfevents.1709399740.n5qclzvvia.422.0 +2 -2
  5. runs/Mar02_17-15-34_n5qclzvvia/events.out.tfevents.1709404316.n5qclzvvia.422.1 +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: 1.2315
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- - Rouge1: 52.3537
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- - Rouge2: 31.6854
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- - Rougel: 36.6454
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- - Rougelsum: 50.8292
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  ## Model description
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@@ -52,31 +52,31 @@ 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 | 25 | 0.6966 | 51.835 | 31.057 | 37.6234 | 50.2076 |
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- | 0.6673 | 2.0 | 50 | 0.6823 | 48.381 | 28.6493 | 37.1777 | 46.9784 |
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- | 0.5505 | 3.0 | 75 | 0.6825 | 51.1061 | 31.5147 | 38.5282 | 49.8741 |
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- | 0.5505 | 4.0 | 100 | 0.7131 | 51.0351 | 32.3268 | 39.7744 | 49.4893 |
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- | 0.4736 | 5.0 | 125 | 0.6975 | 52.9068 | 32.4415 | 39.5503 | 51.2993 |
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- | 0.4033 | 6.0 | 150 | 0.7925 | 51.3766 | 30.4233 | 37.7124 | 49.5155 |
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- | 0.3306 | 7.0 | 175 | 0.8079 | 52.2073 | 31.8487 | 38.6156 | 50.8166 |
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- | 0.3306 | 8.0 | 200 | 0.9168 | 51.6434 | 31.3338 | 37.4811 | 50.1527 |
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- | 0.256 | 9.0 | 225 | 0.9810 | 49.7984 | 30.3608 | 36.7693 | 48.7107 |
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- | 0.1823 | 10.0 | 250 | 0.9289 | 51.679 | 31.2458 | 36.4793 | 50.2032 |
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- | 0.1355 | 11.0 | 275 | 1.0269 | 52.0775 | 31.1824 | 37.5405 | 50.5995 |
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- | 0.1355 | 12.0 | 300 | 1.0736 | 51.3365 | 31.2121 | 38.37 | 50.0703 |
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- | 0.0974 | 13.0 | 325 | 1.0935 | 52.4146 | 32.5704 | 38.0578 | 51.424 |
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- | 0.0681 | 14.0 | 350 | 1.1100 | 51.5136 | 31.6307 | 38.5212 | 50.2267 |
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- | 0.0476 | 15.0 | 375 | 1.1507 | 51.9246 | 31.5588 | 36.8706 | 50.7219 |
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- | 0.0476 | 16.0 | 400 | 1.1667 | 53.7686 | 33.3238 | 38.145 | 52.2277 |
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- | 0.0336 | 17.0 | 425 | 1.1606 | 51.9682 | 31.4379 | 37.6764 | 50.8294 |
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- | 0.0232 | 18.0 | 450 | 1.1961 | 51.6253 | 31.6575 | 37.5128 | 50.406 |
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- | 0.0232 | 19.0 | 475 | 1.2162 | 51.7758 | 31.8239 | 36.3796 | 50.3009 |
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- | 0.0182 | 20.0 | 500 | 1.2315 | 52.3537 | 31.6854 | 36.6454 | 50.8292 |
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  ### Framework versions
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- - Transformers 4.38.1
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  - Pytorch 2.2.1+cu121
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- - Datasets 2.17.1
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  - Tokenizers 0.15.2
 
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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: 1.1824
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+ - Rouge1: 50.8184
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+ - Rouge2: 30.1612
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+ - Rougel: 36.9904
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+ - Rougelsum: 49.4235
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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 | 34 | 0.7061 | 44.9133 | 26.0507 | 34.7329 | 43.2231 |
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+ | 0.8927 | 2.0 | 68 | 0.7190 | 46.3702 | 26.952 | 36.2244 | 44.7608 |
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+ | 0.617 | 3.0 | 102 | 0.6815 | 50.5658 | 28.4213 | 36.4503 | 49.3129 |
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+ | 0.617 | 4.0 | 136 | 0.7083 | 50.7172 | 28.1621 | 37.0023 | 49.3293 |
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+ | 0.5169 | 5.0 | 170 | 0.6819 | 50.0364 | 27.5729 | 35.9607 | 48.0331 |
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+ | 0.4614 | 6.0 | 204 | 0.7171 | 51.0974 | 29.0043 | 36.4498 | 49.6124 |
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+ | 0.3995 | 7.0 | 238 | 0.7577 | 50.8879 | 29.3509 | 35.9144 | 49.4029 |
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+ | 0.3995 | 8.0 | 272 | 0.8192 | 50.332 | 28.9931 | 36.458 | 48.8301 |
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+ | 0.3185 | 9.0 | 306 | 0.8635 | 49.4501 | 27.6673 | 35.7586 | 47.891 |
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+ | 0.2627 | 10.0 | 340 | 0.9229 | 51.0907 | 30.1515 | 36.5669 | 49.6126 |
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+ | 0.2627 | 11.0 | 374 | 0.9910 | 49.6877 | 29.4712 | 36.5784 | 48.6087 |
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+ | 0.1952 | 12.0 | 408 | 1.0266 | 51.3167 | 30.619 | 36.5097 | 49.7864 |
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+ | 0.1234 | 13.0 | 442 | 1.0313 | 49.6518 | 28.2854 | 35.9773 | 48.4327 |
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+ | 0.0859 | 14.0 | 476 | 1.0791 | 50.3139 | 29.9343 | 35.8756 | 49.0233 |
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+ | 0.0859 | 15.0 | 510 | 1.1431 | 50.4173 | 29.047 | 36.4338 | 48.8672 |
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+ | 0.0591 | 16.0 | 544 | 1.1455 | 51.733 | 30.786 | 37.4082 | 50.4284 |
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+ | 0.0448 | 17.0 | 578 | 1.1353 | 49.5046 | 29.3628 | 36.2758 | 48.324 |
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+ | 0.0341 | 18.0 | 612 | 1.1619 | 51.7577 | 31.1043 | 37.9571 | 50.6969 |
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+ | 0.0341 | 19.0 | 646 | 1.1748 | 51.4652 | 30.6309 | 36.7434 | 49.9184 |
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+ | 0.0255 | 20.0 | 680 | 1.1824 | 50.8184 | 30.1612 | 36.9904 | 49.4235 |
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  ### Framework versions
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+ - Transformers 4.38.2
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  - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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  - Tokenizers 0.15.2
generation_config.json CHANGED
@@ -11,6 +11,6 @@
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  "no_repeat_ngram_size": 3,
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  "num_beams": 4,
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  "pad_token_id": 1,
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- "transformers_version": "4.38.1",
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  "use_cache": false
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  }
 
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  "no_repeat_ngram_size": 3,
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  "num_beams": 4,
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  "pad_token_id": 1,
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+ "transformers_version": "4.38.2",
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  "use_cache": false
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  }
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