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pegasus-cnn_dailymail-finetuned-roundup

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+ ---
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: pegasus-cnn_dailymail-finetuned-roundup
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # pegasus-cnn_dailymail-finetuned-roundup
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+
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+ This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9488
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+ - Rouge1: 55.4754
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+ - Rouge2: 39.1074
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+ - Rougel: 40.822
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+ - Rougelsum: 47.3045
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+ - Gen Len: 126.7778
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 16
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
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+ | 1.8482 | 1.0 | 795 | 1.3177 | 51.1349 | 32.0791 | 34.4191 | 41.2001 | 127.0 |
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+ | 1.362 | 2.0 | 1590 | 1.1975 | 52.1955 | 33.7858 | 36.2998 | 42.5368 | 127.0 |
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+ | 1.2847 | 3.0 | 2385 | 1.1299 | 53.3694 | 35.9817 | 39.2437 | 45.2062 | 127.0 |
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+ | 1.1673 | 4.0 | 3180 | 1.0903 | 53.3629 | 35.173 | 37.7775 | 44.3446 | 126.8889 |
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+ | 1.0943 | 5.0 | 3975 | 1.0525 | 54.6538 | 37.3115 | 39.5883 | 46.8043 | 127.0 |
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+ | 1.0615 | 6.0 | 4770 | 1.0317 | 54.6794 | 36.7147 | 39.5731 | 45.8527 | 127.0 |
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+ | 0.993 | 7.0 | 5565 | 1.0144 | 55.2425 | 38.3984 | 41.1723 | 47.266 | 126.8704 |
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+ | 0.9705 | 8.0 | 6360 | 0.9993 | 55.3351 | 38.3237 | 40.4765 | 47.3272 | 127.0 |
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+ | 0.9266 | 9.0 | 7155 | 0.9864 | 55.174 | 38.0535 | 40.3484 | 46.7058 | 126.0926 |
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+ | 0.9181 | 10.0 | 7950 | 0.9713 | 54.822 | 37.8024 | 40.0583 | 46.4962 | 126.5 |
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+ | 0.9053 | 11.0 | 8745 | 0.9690 | 55.6235 | 38.9253 | 40.6261 | 47.1602 | 127.0 |
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+ | 0.8513 | 12.0 | 9540 | 0.9614 | 55.3525 | 38.9343 | 40.4011 | 46.9631 | 127.0 |
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+ | 0.8436 | 13.0 | 10335 | 0.9565 | 56.1316 | 39.5794 | 41.4653 | 47.7626 | 127.0 |
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+ | 0.8343 | 14.0 | 11130 | 0.9522 | 55.7155 | 38.9484 | 40.968 | 47.0273 | 126.7778 |
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+ | 0.8308 | 15.0 | 11925 | 0.9502 | 55.7195 | 39.1268 | 40.7967 | 47.1869 | 127.0 |
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+ | 0.8296 | 16.0 | 12720 | 0.9488 | 55.4754 | 39.1074 | 40.822 | 47.3045 | 126.7778 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.23.1
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 2.6.1
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+ - Tokenizers 0.13.1