metadata
base_model: google/pegasus-cnn_dailymail
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: pegasus-samsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
split: validation
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 0.4616
pegasus-samsum
This model is a fine-tuned version of google/pegasus-cnn_dailymail on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.3665
- Rouge1: 0.4616
- Rouge2: 0.2275
- Rougel: 0.3725
- Rougelsum: 0.3738
- Gen Len: 35.6667
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: 5.750420024069848e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.2186 | 0.87 | 100 | 1.7567 | 0.3571 | 0.1437 | 0.2779 | 0.2797 | 46.7733 |
| 1.7368 | 1.74 | 200 | 1.4933 | 0.4347 | 0.2053 | 0.3459 | 0.3461 | 35.4533 |
| 1.6744 | 2.61 | 300 | 1.4059 | 0.4547 | 0.2179 | 0.3629 | 0.3634 | 35.68 |
| 1.5978 | 3.47 | 400 | 1.3665 | 0.4616 | 0.2275 | 0.3725 | 0.3738 | 35.6667 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3