metadata
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: t5-small-finetuned-cnn-news
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: cnn_dailymail
type: cnn_dailymail
args: 3.0.0
metrics:
- name: Rouge1
type: rouge
value: 24.7231
t5-small-finetuned-cnn-news
This model is a fine-tuned version of t5-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:
- Loss: 1.8412
- Rouge1: 24.7231
- Rouge2: 12.292
- Rougel: 20.5347
- Rougelsum: 23.4668
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: 0.00056
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.0318 | 1.0 | 718 | 1.8028 | 24.5415 | 12.0907 | 20.5343 | 23.3386 |
| 1.8307 | 2.0 | 1436 | 1.8028 | 24.0965 | 11.6367 | 20.2078 | 22.8138 |
| 1.6881 | 3.0 | 2154 | 1.8136 | 25.0822 | 12.6509 | 20.9523 | 23.8303 |
| 1.5778 | 4.0 | 2872 | 1.8269 | 24.4271 | 11.8443 | 20.2281 | 23.0941 |
| 1.501 | 5.0 | 3590 | 1.8412 | 24.7231 | 12.292 | 20.5347 | 23.4668 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1