asril-pegasus
This model is a fine-tuned version of google/pegasus-xsum on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0562
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.4062 | 0.1046 | 1000 | 1.3928 |
1.5209 | 0.2092 | 2000 | 1.2535 |
1.3845 | 0.3138 | 3000 | 1.1791 |
1.3249 | 0.4184 | 4000 | 1.1339 |
1.275 | 0.5230 | 5000 | 1.1066 |
1.235 | 0.6275 | 6000 | 1.0857 |
1.2299 | 0.7321 | 7000 | 1.0743 |
1.2036 | 0.8367 | 8000 | 1.0645 |
1.2115 | 0.9413 | 9000 | 1.0579 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
google/pegasus-xsum