pegasus-legalease
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: 1.1372
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.09 | 250 | 4.9954 |
| 5.2592 | 0.18 | 500 | 4.3175 |
| 5.2592 | 0.27 | 750 | 1.3074 |
| 2.3819 | 0.35 | 1000 | 1.1987 |
| 2.3819 | 0.44 | 1250 | 1.1678 |
| 1.3113 | 0.53 | 1500 | 1.1491 |
| 1.3113 | 0.62 | 1750 | 1.1369 |
| 1.2158 | 0.71 | 2000 | 1.1273 |
| 1.2158 | 0.8 | 2250 | 1.1165 |
| 1.2119 | 0.89 | 2500 | 1.1137 |
| 1.2119 | 0.98 | 2750 | 1.1147 |
| 1.2307 | 1.06 | 3000 | 1.1210 |
| 1.2307 | 1.15 | 3250 | 1.1246 |
| 1.2107 | 1.24 | 3500 | 1.1269 |
| 1.2107 | 1.33 | 3750 | 1.1372 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
google/pegasus-xsum