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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: LifePrincipalPegasusLarge |
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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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# LifePrincipalPegasusLarge |
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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: 5.6547 |
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- Rouge1: 43.3679 |
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- Rouge2: 10.9243 |
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- Rougel: 27.4864 |
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- Rougelsum: 40.3896 |
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- Gen Len: 227.7642 |
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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: 5e-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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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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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: 500 |
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- num_epochs: 1 |
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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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| 6.8795 | 0.0881 | 100 | 6.5014 | 32.7482 | 6.8933 | 21.4622 | 30.1026 | 227.7642 | |
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| 6.4726 | 0.1762 | 200 | 6.2112 | 37.0799 | 8.9306 | 24.652 | 34.5305 | 227.7642 | |
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| 6.2749 | 0.2643 | 300 | 6.0775 | 38.9836 | 9.7478 | 25.6809 | 36.2375 | 227.7642 | |
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| 6.2445 | 0.3524 | 400 | 5.9878 | 39.9961 | 10.0625 | 25.9686 | 37.4853 | 227.7642 | |
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| 6.1752 | 0.4405 | 500 | 5.8898 | 40.1077 | 10.1194 | 26.1056 | 37.4283 | 227.7642 | |
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| 6.0343 | 0.5286 | 600 | 5.8116 | 41.7626 | 10.4065 | 26.7348 | 38.9953 | 227.7642 | |
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| 6.0009 | 0.6167 | 700 | 5.7529 | 42.0869 | 10.5523 | 26.9037 | 39.3663 | 227.7642 | |
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| 5.9523 | 0.7048 | 800 | 5.7057 | 42.4863 | 10.6188 | 27.1573 | 39.6282 | 227.7642 | |
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| 5.9445 | 0.7929 | 900 | 5.6786 | 42.4071 | 10.6897 | 27.1549 | 39.5086 | 227.7642 | |
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| 5.8047 | 0.8810 | 1000 | 5.6646 | 43.4098 | 10.9746 | 27.4646 | 40.4014 | 227.7642 | |
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| 5.8718 | 0.9691 | 1100 | 5.6547 | 43.3679 | 10.9243 | 27.4864 | 40.3896 | 227.7642 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.2.1 |
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- Tokenizers 0.19.1 |
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