pegasus-samsum
This model is a fine-tuned version of google/pegasus-cnn_dailymail on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.3775
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.0058 | 0.1086 | 100 | 1.6564 |
1.6976 | 0.2172 | 200 | 1.5318 |
1.6041 | 0.3258 | 300 | 1.4837 |
1.6314 | 0.4344 | 400 | 1.4586 |
1.6014 | 0.5430 | 500 | 1.4401 |
1.6482 | 0.6516 | 600 | 1.4302 |
1.6023 | 0.7602 | 700 | 1.4151 |
1.621 | 0.8689 | 800 | 1.4111 |
1.5236 | 0.9775 | 900 | 1.4033 |
1.4723 | 1.0858 | 1000 | 1.4004 |
1.4854 | 1.1944 | 1100 | 1.3961 |
1.4423 | 1.3030 | 1200 | 1.3924 |
1.5885 | 1.4116 | 1300 | 1.3860 |
1.4873 | 1.5202 | 1400 | 1.3853 |
1.4214 | 1.6288 | 1500 | 1.3801 |
1.3327 | 1.7374 | 1600 | 1.3794 |
1.4677 | 1.8460 | 1700 | 1.3781 |
1.4413 | 1.9547 | 1800 | 1.3775 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for NandiniRangass/pegasus-samsum
Base model
google/pegasus-cnn_dailymail