results
This model is a fine-tuned version of sshleifer/distill-pegasus-xsum-16-4 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4473
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
7.2378 | 0.51 | 100 | 7.1853 |
7.2309 | 1.01 | 200 | 6.6342 |
6.4796 | 1.52 | 300 | 6.3206 |
6.2691 | 2.02 | 400 | 6.0184 |
5.7382 | 2.53 | 500 | 5.5754 |
4.9922 | 3.03 | 600 | 4.5178 |
3.6031 | 3.54 | 700 | 2.8579 |
2.5203 | 4.04 | 800 | 2.4718 |
2.2563 | 4.55 | 900 | 2.4128 |
2.1425 | 5.05 | 1000 | 2.3767 |
2.004 | 5.56 | 1100 | 2.3982 |
2.0437 | 6.06 | 1200 | 2.3787 |
1.9407 | 6.57 | 1300 | 2.3952 |
1.9194 | 7.07 | 1400 | 2.3964 |
1.758 | 7.58 | 1500 | 2.4056 |
1.918 | 8.08 | 1600 | 2.4101 |
1.9162 | 8.59 | 1700 | 2.4085 |
1.8983 | 9.09 | 1800 | 2.4058 |
1.6939 | 9.6 | 1900 | 2.4050 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 1.15.1
- Tokenizers 0.10.3
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