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bart-large-cnn-finetuned-scope-summarization

Text2Text Generation
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bart
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  1. README.md +29 -29
  2. generation_config.json +1 -1
  3. model.safetensors +1 -1
  4. runs/Apr22_20-56-53_niyi1h1ros/events.out.tfevents.1713819629.niyi1h1ros.307.0 +2 -2
  5. runs/Apr22_20-56-53_niyi1h1ros/events.out.tfevents.1713823067.niyi1h1ros.307.1 +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: 0.0552
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- - Rouge1: 49.8374
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- - Rouge2: 38.0885
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- - Rougel: 42.6985
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- - Rougelsum: 42.4809
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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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- | 0.6831 | 1.0 | 43 | 0.3928 | 40.6965 | 25.3494 | 30.1716 | 29.9938 |
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- | 0.3578 | 2.0 | 86 | 0.3598 | 43.284 | 27.9071 | 32.9941 | 32.9077 |
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- | 0.3302 | 3.0 | 129 | 0.3362 | 45.2375 | 30.4709 | 34.8733 | 34.6801 |
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- | 0.309 | 4.0 | 172 | 0.3136 | 44.928 | 30.8601 | 34.7804 | 34.6754 |
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- | 0.2948 | 5.0 | 215 | 0.2919 | 44.5169 | 30.2429 | 34.5979 | 34.4672 |
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- | 0.2841 | 6.0 | 258 | 0.2755 | 45.7172 | 31.6555 | 34.9668 | 34.9069 |
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- | 0.268 | 7.0 | 301 | 0.2618 | 46.4085 | 32.782 | 35.804 | 35.6348 |
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- | 0.252 | 8.0 | 344 | 0.2424 | 47.8634 | 33.6728 | 36.9559 | 36.9081 |
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- | 0.2405 | 9.0 | 387 | 0.2286 | 46.8182 | 34.4363 | 37.7534 | 37.6356 |
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- | 0.2255 | 10.0 | 430 | 0.2276 | 46.8516 | 33.3166 | 37.6246 | 37.5024 |
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- | 0.2125 | 11.0 | 473 | 0.1946 | 47.6772 | 33.9627 | 37.8554 | 37.7735 |
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- | 0.1918 | 12.0 | 516 | 0.1682 | 46.851 | 33.6098 | 38.2906 | 38.24 |
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- | 0.1726 | 13.0 | 559 | 0.1442 | 48.8833 | 36.4235 | 39.4263 | 39.1955 |
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- | 0.152 | 14.0 | 602 | 0.1305 | 50.5835 | 39.2008 | 43.3793 | 43.1671 |
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- | 0.1344 | 15.0 | 645 | 0.1109 | 47.3517 | 35.4446 | 38.0845 | 38.0578 |
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- | 0.116 | 16.0 | 688 | 0.0842 | 48.9774 | 37.6705 | 41.6306 | 41.4792 |
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- | 0.1007 | 17.0 | 731 | 0.0762 | 49.9775 | 38.4186 | 42.647 | 42.4334 |
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- | 0.0899 | 18.0 | 774 | 0.0623 | 50.1358 | 38.9943 | 43.4025 | 43.1603 |
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- | 0.0805 | 19.0 | 817 | 0.0571 | 51.5974 | 40.1928 | 44.1821 | 43.9354 |
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- | 0.0753 | 20.0 | 860 | 0.0552 | 49.8374 | 38.0885 | 42.6985 | 42.4809 |
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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
 
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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: 0.0243
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+ - Rouge1: 55.9358
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+ - Rouge2: 45.6813
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+ - Rougel: 49.2605
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+ - Rougelsum: 49.2571
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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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+ | 0.6983 | 1.0 | 40 | 0.2685 | 44.58 | 29.0429 | 33.1495 | 33.1669 |
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+ | 0.2633 | 2.0 | 80 | 0.2441 | 43.3662 | 28.4897 | 33.4037 | 33.4937 |
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+ | 0.237 | 3.0 | 120 | 0.2337 | 45.9311 | 31.605 | 36.3412 | 36.4591 |
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+ | 0.225 | 4.0 | 160 | 0.2181 | 44.6684 | 30.2624 | 33.897 | 34.0548 |
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+ | 0.2021 | 5.0 | 200 | 0.2001 | 47.4399 | 33.8502 | 37.3868 | 37.5961 |
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+ | 0.2052 | 6.0 | 240 | 0.1894 | 49.5407 | 34.8779 | 38.7442 | 38.9632 |
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+ | 0.181 | 7.0 | 280 | 0.1772 | 50.5942 | 37.1982 | 39.6862 | 39.9688 |
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+ | 0.1764 | 8.0 | 320 | 0.1724 | 48.7175 | 34.9565 | 39.7672 | 40.0419 |
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+ | 0.1626 | 9.0 | 360 | 0.1568 | 49.6688 | 36.5888 | 40.6817 | 41.0034 |
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+ | 0.1429 | 10.0 | 400 | 0.1324 | 51.4759 | 39.2328 | 43.5475 | 43.6525 |
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+ | 0.1338 | 11.0 | 440 | 0.1206 | 50.0612 | 37.7502 | 42.3231 | 42.4899 |
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+ | 0.1142 | 12.0 | 480 | 0.0899 | 52.8525 | 40.2391 | 45.0142 | 45.1042 |
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+ | 0.1004 | 13.0 | 520 | 0.0706 | 54.8157 | 43.1336 | 46.6612 | 46.6237 |
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+ | 0.086 | 14.0 | 560 | 0.0564 | 55.0703 | 43.5883 | 47.3974 | 47.5532 |
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+ | 0.0695 | 15.0 | 600 | 0.0451 | 53.8285 | 44.1487 | 48.4204 | 48.5559 |
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+ | 0.0594 | 16.0 | 640 | 0.0357 | 55.0319 | 43.9487 | 47.9211 | 47.969 |
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+ | 0.0508 | 17.0 | 680 | 0.0346 | 56.3059 | 45.3574 | 49.1356 | 49.2768 |
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+ | 0.04 | 18.0 | 720 | 0.0279 | 57.2262 | 46.371 | 50.2692 | 50.2699 |
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+ | 0.0358 | 19.0 | 760 | 0.0259 | 55.606 | 45.1493 | 49.3667 | 49.4148 |
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+ | 0.0337 | 20.0 | 800 | 0.0243 | 55.9358 | 45.6813 | 49.2605 | 49.2571 |
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  ### Framework versions
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.2+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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": "4.38.2",
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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": "4.40.0",
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  "use_cache": false
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  }
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