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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- samsum |
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model-index: |
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- name: pegasus-samsum-1 |
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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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# pegasus-samsum-1 |
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This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3783 |
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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: 2 |
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- total_train_batch_size: 2 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.7182 | 0.07 | 500 | 1.6019 | |
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| 1.805 | 0.14 | 1000 | 1.5057 | |
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| 1.7421 | 0.2 | 1500 | 1.4710 | |
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| 1.4131 | 0.27 | 2000 | 1.4522 | |
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| 1.5483 | 0.34 | 2500 | 1.4422 | |
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| 1.2689 | 0.41 | 3000 | 1.4297 | |
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| 2.0376 | 0.48 | 3500 | 1.4136 | |
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| 1.5208 | 0.54 | 4000 | 1.4089 | |
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| 1.6772 | 0.61 | 4500 | 1.3973 | |
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| 1.5757 | 0.68 | 5000 | 1.3951 | |
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| 1.8022 | 0.75 | 5500 | 1.3846 | |
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| 1.6937 | 0.81 | 6000 | 1.3833 | |
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| 1.4412 | 0.88 | 6500 | 1.3820 | |
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| 1.4339 | 0.95 | 7000 | 1.3783 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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