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
- Downloads last month
- 10
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for jwhong2006/wikisum
Base model
google-t5/t5-small