metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- arxiv_summarization_dataset
metrics:
- rouge
base_model: sshleifer/distilbart-cnn-12-6
model-index:
- name: distilbart-cnn-12-6-finetuned-30k-3epoch
results:
- task:
type: text2text-generation
name: Sequence-to-sequence Language Modeling
dataset:
name: arxiv_summarization_dataset
type: arxiv_summarization_dataset
config: section
split: test[:2000]
args: section
metrics:
- type: rouge
value: 43.696
name: Rouge1
distilbart-cnn-12-6-finetuned-30k-3epoch
This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on the arxiv_summarization_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 2.3411
- Rouge1: 43.696
- Rouge2: 15.6681
- Rougel: 25.6889
- Rougelsum: 38.574
- Gen Len: 121.98
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.7304 | 1.0 | 3750 | 2.4322 | 43.0913 | 15.1302 | 25.2555 | 38.0346 | 122.3755 |
| 2.3518 | 2.0 | 7500 | 2.3613 | 43.8799 | 15.6977 | 25.6984 | 38.7646 | 122.6945 |
| 2.2318 | 3.0 | 11250 | 2.3411 | 43.696 | 15.6681 | 25.6889 | 38.574 | 121.98 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3