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--- |
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license: mit |
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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 |
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results: [] |
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datasets: |
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- samsum |
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metrics: |
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- rouge |
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library_name: transformers |
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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 |
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4963 |
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## Model description |
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Original bart (Bidirectional Auto Regressive Transformers) paper : https://arxiv.org/abs/1910.13461 |
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## Training and evaluation data |
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Fine-Tuned over 1 epoch. The improvements over facebook/bart-large-cnn over the rouge benchmark is as follows : <br> |
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Rouge1 : 30.6 % <br> |
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Rouge2 : 103 % <br> |
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RougeL : 33.18 % <br> |
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RougeLSum : 33.18 % <br> |
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## Training procedure |
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Please refer to https://github.com/dhivyeshrk/FineTuning-Facebook-bart-large-cnn |
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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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| 1.3689 | 0.54 | 500 | 1.4963 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
