metadata
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-legalease
results: []
datasets:
- hheiden/us-congress-117-bills
pegasus-legalease
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.2373
- Rouge1: 0.4847
- Rouge2: 0.3225
- Rougel: 0.4194
- Rougelsum: 0.4177
- Gen Len: 43.02
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
5.2738 | 1.0 | 125 | 4.6004 | 0.4363 | 0.2769 | 0.375 | 0.3743 | 37.24 |
4.8164 | 2.0 | 250 | 4.4350 | 0.464 | 0.3085 | 0.405 | 0.4038 | 40.3 |
4.8494 | 3.0 | 375 | 4.3372 | 0.473 | 0.3153 | 0.412 | 0.41 | 41.2 |
4.6062 | 4.0 | 500 | 4.2669 | 0.4791 | 0.3196 | 0.4159 | 0.4141 | 43.03 |
4.5682 | 5.0 | 625 | 4.2373 | 0.4847 | 0.3225 | 0.4194 | 0.4177 | 43.02 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2