metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: wikisum
results: []
datasets:
- d0rj/wikisum
language:
- en
library_name: transformers
pipeline_tag: summarization
wikisum
This model is a fine-tuned version of t5-small on an wikisum dataset. It achieves the following results on the evaluation set:
- Loss: 2.2922
- Rouge1: 0.1811
- Rouge2: 0.0673
- Rougel: 0.147
- Rougelsum: 0.147
- Gen Len: 19.0
Model description
t5-small model fine-tuned on wikisum dataset.
Intended uses & limitations
Intended use: sumamrization of informatic articles. Limitations : may generate misleading information.
Training and evaluation data
check out wikisum dataset
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.5807 | 0.2236 | 500 | 2.3647 | 0.1813 | 0.0635 | 0.1452 | 0.1453 | 19.0 |
| 2.5059 | 0.4472 | 1000 | 2.3190 | 0.1823 | 0.0663 | 0.1473 | 0.1473 | 19.0 |
| 2.4945 | 0.6708 | 1500 | 2.3003 | 0.1808 | 0.0666 | 0.1468 | 0.1467 | 19.0 |
| 2.4963 | 0.8945 | 2000 | 2.2922 | 0.1811 | 0.0673 | 0.147 | 0.147 | 19.0 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1