---
tags:
- generated_from_trainer
datasets:
- big_patent
metrics:
- rouge
model-index:
- name: nd_pegasus_bigpatent_cnn_xsum_model
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: big_patent
      type: big_patent
      config: d
      split: train[:200]
      args: d
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.3465
---

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# nd_pegasus_bigpatent_cnn_xsum_model

This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the big_patent dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1037
- Rouge1: 0.3465
- Rouge2: 0.1181
- Rougel: 0.2258
- Rougelsum: 0.227
- Gen Len: 85.75

## 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: 2
- eval_batch_size: 2
- 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 3.5734        | 1.0   | 80   | 3.1804          | 0.3468 | 0.1231 | 0.2262 | 0.2268    | 89.95   |
| 3.3146        | 2.0   | 160  | 3.1037          | 0.3465 | 0.1181 | 0.2258 | 0.227     | 85.75   |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2