tidy-tab-model-pegasus-xsum
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: 0.9644
- Rouge1: 0.7456
- Rouge2: 0.6153
- Rougel: 0.7401
- Rougelsum: 0.7422
- Gen Len: 5.2607
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.5893 | 3.7879 | 500 | 1.0234 | 0.7302 | 0.594 | 0.7229 | 0.7244 | 5.3034 |
| 0.9308 | 7.5758 | 1000 | 0.9644 | 0.7456 | 0.6153 | 0.7401 | 0.7422 | 5.2607 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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