metadata
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: t5-small-finetuned-summarization-cnn
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: cnn_dailymail
type: cnn_dailymail
config: 3.0.0
split: train[:2%]
args: 3.0.0
metrics:
- name: Rouge1
type: rouge
value: 24.4825
t5-small-finetuned-summarization-cnn
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: 2.0105
- Rouge1: 24.4825
- Rouge2: 9.1573
- Rougel: 19.7135
- Rougelsum: 22.2551
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: 5.6e-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: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
2.0389 | 1.0 | 718 | 2.0150 | 24.4413 | 9.1782 | 19.7202 | 22.2225 |
1.9497 | 2.0 | 1436 | 2.0105 | 24.4825 | 9.1573 | 19.7135 | 22.2551 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2