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bart-large-cnn-finetuned-scope-summarization

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  1. README.md +15 -15
  2. model.safetensors +1 -1
  3. runs/Apr29_10-13-40_nszdm79wsj/events.out.tfevents.1714385677.nszdm79wsj.243.0 +3 -0
  4. runs/Apr29_10-13-40_nszdm79wsj/events.out.tfevents.1714387422.nszdm79wsj.243.1 +3 -0
  5. training_args.bin +1 -1
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: 0.1308
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- - Rouge1: 49.6683
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- - Rouge2: 37.3929
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- - Rougel: 41.666
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- - Rougelsum: 41.5602
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  ## Model description
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@@ -52,16 +52,16 @@ 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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- | 0.696 | 1.0 | 40 | 0.2500 | 43.2634 | 27.0334 | 33.128 | 32.9348 |
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- | 0.2625 | 2.0 | 80 | 0.2228 | 42.4679 | 27.647 | 31.9258 | 31.7877 |
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- | 0.2425 | 3.0 | 120 | 0.2082 | 44.0252 | 30.8098 | 33.9707 | 33.9697 |
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- | 0.2266 | 4.0 | 160 | 0.1936 | 45.3968 | 32.4864 | 36.0748 | 35.9962 |
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- | 0.2031 | 5.0 | 200 | 0.1823 | 47.2956 | 34.832 | 38.3544 | 38.2526 |
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- | 0.2056 | 6.0 | 240 | 0.1677 | 46.3752 | 34.4471 | 37.3837 | 37.262 |
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- | 0.1819 | 7.0 | 280 | 0.1570 | 47.8024 | 35.2228 | 39.4649 | 39.3768 |
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- | 0.1762 | 8.0 | 320 | 0.1461 | 47.9403 | 37.0271 | 41.7617 | 41.6654 |
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- | 0.1637 | 9.0 | 360 | 0.1376 | 48.2515 | 36.0442 | 40.149 | 40.0905 |
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- | 0.1484 | 10.0 | 400 | 0.1308 | 49.6683 | 37.3929 | 41.666 | 41.5602 |
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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: 0.1538
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+ - Rouge1: 53.2487
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+ - Rouge2: 38.8678
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+ - Rougel: 42.9164
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+ - Rougelsum: 42.8185
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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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+ | 0.6973 | 1.0 | 40 | 0.2792 | 44.607 | 28.2305 | 32.7363 | 32.689 |
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+ | 0.2634 | 2.0 | 80 | 0.2542 | 44.9628 | 28.6393 | 35.5185 | 35.5316 |
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+ | 0.237 | 3.0 | 120 | 0.2347 | 48.3923 | 32.1964 | 37.0858 | 37.0633 |
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+ | 0.2241 | 4.0 | 160 | 0.2234 | 50.2514 | 34.1207 | 38.6719 | 38.6132 |
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+ | 0.2011 | 5.0 | 200 | 0.2091 | 52.4212 | 36.8234 | 40.958 | 40.9959 |
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+ | 0.2045 | 6.0 | 240 | 0.1958 | 52.1925 | 37.8449 | 42.6498 | 42.6355 |
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+ | 0.1797 | 7.0 | 280 | 0.1806 | 53.0427 | 38.3417 | 41.5969 | 41.5104 |
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+ | 0.1746 | 8.0 | 320 | 0.1701 | 53.1042 | 38.8772 | 43.3092 | 43.2253 |
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+ | 0.162 | 9.0 | 360 | 0.1620 | 52.5124 | 38.3429 | 42.1167 | 42.0158 |
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+ | 0.1471 | 10.0 | 400 | 0.1538 | 53.2487 | 38.8678 | 42.9164 | 42.8185 |
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  ### Framework versions
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