metadata
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- summarization
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: t5-small-Abstractive-Summarizer
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: multi_news
type: multi_news
config: default
split: validation
args: default
metrics:
- name: Rouge1
type: rouge
value: 15.7032
t5-small-Abstractive-Summarizer
This model is a fine-tuned version of t5-small on the multi_news dataset. It achieves the following results on the evaluation set:
- Loss: 2.7737
- Rouge1: 15.7032
- Rouge2: 5.2433
- Rougel: 12.282
- Rougelsum: 14.0946
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 |
|---|---|---|---|---|---|---|---|
| 3.118 | 1.0 | 113 | 2.7677 | 15.1343 | 4.7712 | 11.8812 | 13.386 |
| 2.7857 | 2.0 | 226 | 2.7609 | 15.7641 | 4.8705 | 12.0955 | 13.9779 |
| 2.6158 | 3.0 | 339 | 2.7494 | 15.1515 | 4.4523 | 11.7147 | 13.4181 |
| 2.4962 | 4.0 | 452 | 2.7743 | 15.344 | 5.1073 | 12.1574 | 13.7917 |
| 2.4304 | 5.0 | 565 | 2.7737 | 15.7032 | 5.2433 | 12.282 | 14.0946 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1