metadata
tags:
- generated_from_trainer
datasets:
- aeslc
metrics:
- rouge
model-index:
- name: pegasus-large-finetuned-aeslc
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: aeslc
type: aeslc
config: default
split: validation
args: default
metrics:
- name: Rouge1
type: rouge
value: 32.9341
pegasus-large-finetuned-aeslc
This model is a fine-tuned version of google/pegasus-large on the aeslc dataset. It achieves the following results on the evaluation set:
- Loss: 3.0274
- Rouge1: 32.9341
- Rouge2: 17.7876
- Rougel: 32.0858
- Rougelsum: 32.0886
- Gen Len: 11.6577
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 |
---|---|---|---|---|---|---|---|---|
3.3247 | 1.0 | 7218 | 3.0274 | 32.9341 | 17.7876 | 32.0858 | 32.0886 | 11.6577 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3