pegasus-samsum
This model is a fine-tuned version of google/pegasus-large on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.3086
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.6151 | 0.54 | 500 | 1.4238 |
1.3357 | 1.09 | 1000 | 1.3629 |
1.4423 | 1.63 | 1500 | 1.3380 |
1.3747 | 2.17 | 2000 | 1.3218 |
1.3397 | 2.72 | 2500 | 1.3124 |
1.2706 | 3.26 | 3000 | 1.3149 |
1.1849 | 3.8 | 3500 | 1.3120 |
1.2222 | 4.35 | 4000 | 1.3120 |
1.2339 | 4.89 | 4500 | 1.3086 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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