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--- |
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base_model: google/pegasus-large |
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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: results_pegasus2-_wiki |
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results: [] |
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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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# results_pegasus2-_wiki |
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This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0771 |
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- Rouge1: 0.2644 |
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- Rouge2: 0.1159 |
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- Rougel: 0.264 |
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- Rougelsum: 0.2635 |
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- Gen Len: 248.7564 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 4e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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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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- lr_scheduler_warmup_steps: 250 |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:| |
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| 2.6037 | 0.5222 | 500 | 0.2910 | 0.0 | 0.0 | 0.0 | 0.0 | 223.1886 | |
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| 0.2787 | 1.0444 | 1000 | 0.2403 | 0.0515 | 0.0 | 0.0525 | 0.052 | 221.6974 | |
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| 0.2284 | 1.5666 | 1500 | 0.1922 | 0.0607 | 0.0 | 0.0621 | 0.0614 | 246.9666 | |
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| 0.1827 | 2.0888 | 2000 | 0.1775 | 0.1271 | 0.0176 | 0.129 | 0.1278 | 247.4322 | |
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| 0.167 | 2.6110 | 2500 | 0.1437 | 0.1591 | 0.0347 | 0.1597 | 0.1598 | 248.3084 | |
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| 0.1537 | 3.1332 | 3000 | 0.1301 | 0.1765 | 0.047 | 0.1765 | 0.1754 | 249.0864 | |
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| 0.14 | 3.6554 | 3500 | 0.1183 | 0.2082 | 0.059 | 0.2086 | 0.2077 | 248.2633 | |
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| 0.1306 | 4.1775 | 4000 | 0.1092 | 0.2095 | 0.0599 | 0.209 | 0.2083 | 246.5972 | |
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| 0.1272 | 4.6997 | 4500 | 0.1024 | 0.2181 | 0.0719 | 0.2177 | 0.2172 | 247.3752 | |
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| 0.1177 | 5.2219 | 5000 | 0.1013 | 0.2217 | 0.0725 | 0.2217 | 0.2211 | 247.4224 | |
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| 0.1123 | 5.7441 | 5500 | 0.0929 | 0.2242 | 0.0797 | 0.2249 | 0.2243 | 247.277 | |
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| 0.1114 | 6.2663 | 6000 | 0.0887 | 0.2335 | 0.0839 | 0.2334 | 0.233 | 247.3399 | |
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| 0.1073 | 6.7885 | 6500 | 0.0835 | 0.2452 | 0.0976 | 0.2461 | 0.2452 | 249.2043 | |
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| 0.1025 | 7.3107 | 7000 | 0.0821 | 0.2458 | 0.0971 | 0.2456 | 0.2455 | 246.2063 | |
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| 0.1009 | 7.8329 | 7500 | 0.0821 | 0.251 | 0.1009 | 0.2509 | 0.2508 | 248.7642 | |
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| 0.1004 | 8.3551 | 8000 | 0.0834 | 0.2583 | 0.1058 | 0.2587 | 0.258 | 248.7525 | |
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| 0.0965 | 8.8773 | 8500 | 0.0791 | 0.2621 | 0.116 | 0.2622 | 0.2621 | 248.7407 | |
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| 0.0975 | 9.3995 | 9000 | 0.0781 | 0.2619 | 0.1147 | 0.2613 | 0.2608 | 248.4185 | |
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| 0.0941 | 9.9217 | 9500 | 0.0771 | 0.2644 | 0.1159 | 0.264 | 0.2635 | 248.7564 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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