pegasus-samsum
This model is a fine-tuned version of facebook/bart-large-cnn on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4963
Model description
Original bart (Bidirectional Auto Regressive Transformers) paper : https://arxiv.org/abs/1910.13461
Training and evaluation data
Fine-Tuned over 1 epoch. The improvements over facebook/bart-large-cnn over the rouge benchmark is as follows :
Rouge1 : 30.6 %
Rouge2 : 103 %
RougeL : 33.18 %
RougeLSum : 33.18 %
Training procedure
Please refer to https://github.com/dhivyeshrk/FineTuning-Facebook-bart-large-cnn
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3689 | 0.54 | 500 | 1.4963 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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