t5-small-finetuned-multi-news
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: 2.7775
- Rouge1: 14.5549
- Rouge2: 4.5934
- Rougel: 11.1178
- Rougelsum: 12.8964
- Gen Len: 19.0
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.0211 | 1.0 | 1405 | 2.7775 | 14.5549 | 4.5934 | 11.1178 | 12.8964 | 19.0 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
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Dataset used to train nikhedward/t5-small-finetuned-multi-news
Evaluation results
- Rouge1 on multi_newsself-reported14.555