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bart-large-cnn-finetuned-scope-summarization

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  1. README.md +18 -18
  2. config.json +1 -1
  3. generation_config.json +1 -1
  4. model.safetensors +1 -1
  5. runs/Jun18_20-50-06_nhva9sd5jo/events.out.tfevents.1718744436.nhva9sd5jo.455.0 +3 -0
  6. runs/Jun18_20-50-06_nhva9sd5jo/events.out.tfevents.1718748010.nhva9sd5jo.455.1 +3 -0
  7. training_args.bin +2 -2
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: 0.1209
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- - Rouge1: 55.1221
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- - Rouge2: 41.5118
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- - Rougel: 44.1055
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- - Rougelsum: 44.1111
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  ## Model description
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@@ -52,21 +52,21 @@ 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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- | 0.6833 | 1.0 | 40 | 0.2361 | 49.6521 | 32.0116 | 37.6798 | 37.6414 |
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- | 0.2662 | 2.0 | 80 | 0.2113 | 51.0105 | 34.9383 | 38.5987 | 38.7128 |
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- | 0.2372 | 3.0 | 120 | 0.1899 | 49.9708 | 34.1358 | 39.2319 | 39.256 |
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- | 0.2295 | 4.0 | 160 | 0.1781 | 52.0623 | 36.7753 | 39.7153 | 39.7944 |
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- | 0.2022 | 5.0 | 200 | 0.1613 | 53.525 | 37.8889 | 42.8148 | 42.8252 |
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- | 0.204 | 6.0 | 240 | 0.1561 | 54.6369 | 39.0632 | 42.0898 | 42.0239 |
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- | 0.1801 | 7.0 | 280 | 0.1409 | 54.6083 | 39.9751 | 43.8491 | 43.8897 |
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- | 0.175 | 8.0 | 320 | 0.1329 | 54.9258 | 40.6335 | 44.7135 | 44.6887 |
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- | 0.1715 | 9.0 | 360 | 0.1331 | 56.8449 | 41.313 | 43.4297 | 43.56 |
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- | 0.1551 | 10.0 | 400 | 0.1209 | 55.1221 | 41.5118 | 44.1055 | 44.1111 |
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  ### Framework versions
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- - Transformers 4.40.1
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- - Pytorch 2.3.0+cu121
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- - Datasets 2.19.0
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  - Tokenizers 0.19.1
 
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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: 0.1309
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+ - Rouge1: 52.6236
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+ - Rouge2: 39.8632
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+ - Rougel: 43.4607
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+ - Rougelsum: 43.3561
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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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+ | 0.5104 | 1.0 | 34 | 0.2207 | 41.732 | 26.7717 | 31.2807 | 31.3611 |
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+ | 0.2181 | 2.0 | 68 | 0.2001 | 44.5268 | 30.0523 | 34.7912 | 35.0095 |
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+ | 0.1824 | 3.0 | 102 | 0.1995 | 45.4038 | 32.6808 | 36.3856 | 36.4004 |
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+ | 0.1851 | 4.0 | 136 | 0.1728 | 48.85 | 35.9202 | 39.2826 | 39.1813 |
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+ | 0.1692 | 5.0 | 170 | 0.1663 | 47.1374 | 34.5505 | 37.8192 | 37.8176 |
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+ | 0.164 | 6.0 | 204 | 0.1594 | 50.3895 | 37.8751 | 40.4181 | 40.3778 |
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+ | 0.1534 | 7.0 | 238 | 0.1526 | 50.7178 | 38.8207 | 41.5719 | 41.6111 |
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+ | 0.1421 | 8.0 | 272 | 0.1424 | 51.3382 | 38.6796 | 40.4545 | 40.3891 |
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+ | 0.1423 | 9.0 | 306 | 0.1354 | 53.8161 | 41.0736 | 45.1571 | 45.0427 |
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+ | 0.1336 | 10.0 | 340 | 0.1309 | 52.6236 | 39.8632 | 43.4607 | 43.3561 |
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  ### Framework versions
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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  - Tokenizers 0.19.1
config.json CHANGED
@@ -65,7 +65,7 @@
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  }
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  },
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  "torch_dtype": "float32",
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- "transformers_version": "4.40.1",
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  "use_cache": false,
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  "vocab_size": 50264
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  }
 
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  }
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  },
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  "torch_dtype": "float32",
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+ "transformers_version": "4.41.2",
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  "use_cache": false,
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  "vocab_size": 50264
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  }
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": "4.40.1",
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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": "4.41.2",
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  "use_cache": false
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  }
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