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theojolliffe/bart-large-cnn-finetuned-roundup-16
bart-large-cnn-finetuned-roundup-16 is a machine learning model from theojolliffe. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 132 | 1.3170 | 48.412 | 29.2017 | 31.6679 | 45.494 | 141.85 |
| No log | 2.0 | 264 | 1.2292 | 49.0133 | 29.6645 | 30.7612 | 46.1673 | 142.0 |
| No log | 3.0 | 396 | 1.2670 | 49.183 | 29.4104 | 31.573 | 46.7082 | 142.0 |
| 0.9596 | 4.0 | 528 | 1.3059 | 47.3854 | 26.6865 | 28.4666 | 44.4934 | 141.8 |
| 0.9596 | 5.0 | 660 | 1.3288 | 48.1189 | 26.9242 | 31.2938 | 45.3462 | 142.0 |
| 0.9596 | 6.0 | 792 | 1.4084 | 47.5713 | 26.7488 | 29.2959 | 45.1764 | 141.3 |
| 0.9596 | 7.0 | 924 | 1.5043 | 46.5407 | 26.0995 | 29.9007 | 43.9335 | 142.0 |
| 0.3369 | 8.0 | 1056 | 1.5115 | 49.6891 | 29.0514 | 32.33 | 46.9357 | 142.0 |
| 0.3369 | 9.0 | 1188 | 1.6131 | 47.5773 | 27.6348 | 30.5294 | 45.1151 | 142.0 |
| 0.3369 | 10.0 | 1320 | 1.6837 | 46.5699 | 26.3805 | 29.8581 | 43.5252 | 142.0 |
| 0.3369 | 11.0 | 1452 | 1.7874 | 47.1383 | 26.535 | 30.1724 | 44.2508 | 142.0 |
| 0.148 | 12.0 | 1584 | 1.7776 | 49.8061 | 30.1994 | 33.2405 | 47.6102 | 142.0 |
| 0.148 | 13.0 | 1716 | 1.8144 | 48.4451 | 28.2949 | 30.9026 | 45.6614 | 142.0 |
| 0.148 | 14.0 | 1848 | 1.8646 | 50.1964 | 30.4426 | 32.8156 | 47.4134 | 142.0 |
| 0.148 | 15.0 | 1980 | 1.8829 | 48.8129 | 29.2358 | 32.3247 | 46.2233 | 142.0 |
| 0.0726 | 16.0 | 2112 | 1.8957 | 49.4097 | 29.3516 | 31.527 | 46.4241 | 141.9 |