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--- |
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base_model: google/pegasus-cnn_dailymail |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: pegasus-samsum-nlp-with-transformers-ch06 |
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results: [] |
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datasets: |
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- samsum |
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language: |
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- en |
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metrics: |
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- rouge |
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pipeline_tag: summarization |
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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-nlp-with-transformers-ch06 |
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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](https://huggingface.co/datasets/samsum) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4839 |
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It achieves the following ROUGE scores on the test set: |
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- rouge1: 0.555556 |
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- rouge2: 0.230769 |
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- rougeL: 0.518519 |
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- rougeLsum: 0.518519 |
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**Quick human evaluation of summarization quality:** the results are generally good, after visual inspection of the summaries generated on test set conversations. However it seems some entities/attributions are incorrect (saw an example where model confuses peoples' roles in multi-person chat) |
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## Model description |
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PEGASUS doc can be found here: [https://huggingface.co/docs/transformers/model_doc/pegasus](https://huggingface.co/docs/transformers/model_doc/pegasus) |
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## Intended uses & limitations |
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This model was trained while studying the NLP With Transformers book; it is not intended to be used for any real applications. |
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## Training and evaluation data |
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The finetuning data is the SAMSum dataset only. |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.6592 | 0.54 | 500 | 1.4839 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
