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---
tags:
- generated_from_trainer
datasets:
- aeslc
metrics:
- rouge
model-index:
- name: pegasus-large-finetuned-aeslc-test
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: aeslc
type: aeslc
config: default
split: test
args: default
metrics:
- name: Rouge1
type: rouge
value: 32.3073
---
<!-- 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-large-finetuned-aeslc-test
This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the aeslc dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1200
- Rouge1: 32.3073
- Rouge2: 17.5238
- Rougel: 31.3366
- Rougelsum: 31.3175
- Gen Len: 11.6343
## 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: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 3.3149 | 1.0 | 7218 | 3.1200 | 32.3073 | 17.5238 | 31.3366 | 31.3175 | 11.6343 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3