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---
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
---
<!-- 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. -->
# 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
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