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---
base_model: google/pegasus-xsum
tags:
- generated_from_trainer
model-index:
- name: pegasus-legalease
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# pegasus-legalease
This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1927
## 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 | 4.7237 |
| 5.061 | 0.18 | 500 | 4.3026 |
| 5.061 | 0.27 | 750 | 2.1449 |
| 2.8599 | 0.35 | 1000 | 1.3299 |
| 2.8599 | 0.44 | 1250 | 1.2940 |
| 1.4864 | 0.53 | 1500 | 1.2739 |
| 1.4864 | 0.62 | 1750 | 1.2594 |
| 1.3623 | 0.71 | 2000 | 1.2481 |
| 1.3623 | 0.8 | 2250 | 1.2395 |
| 1.3454 | 0.89 | 2500 | 1.2323 |
| 1.3454 | 0.98 | 2750 | 1.2245 |
| 1.3478 | 1.06 | 3000 | 1.2168 |
| 1.3478 | 1.15 | 3250 | 1.2128 |
| 1.2904 | 1.24 | 3500 | 1.2079 |
| 1.2904 | 1.33 | 3750 | 1.2048 |
| 1.279 | 1.42 | 4000 | 1.2027 |
| 1.279 | 1.51 | 4250 | 1.1998 |
| 1.2933 | 1.6 | 4500 | 1.1978 |
| 1.2933 | 1.68 | 4750 | 1.1958 |
| 1.2531 | 1.77 | 5000 | 1.1941 |
| 1.2531 | 1.86 | 5250 | 1.1933 |
| 1.2655 | 1.95 | 5500 | 1.1927 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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