t5-small-finetuned-samsum
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7651
- Rouge1: 41.6124
- Rouge2: 18.7668
- Rougel: 35.0271
- Rougelsum: 38.5305
- Gen Len: 16.6381
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: 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.044 | 1.0 | 921 | 1.8159 | 41.1358 | 18.1022 | 34.3309 | 38.1969 | 16.5232 |
| 1.9796 | 2.0 | 1842 | 1.7915 | 41.4713 | 18.6313 | 34.7999 | 38.4147 | 16.566 |
| 1.9487 | 3.0 | 2763 | 1.7724 | 41.6106 | 18.6119 | 34.7796 | 38.5737 | 16.7213 |
| 1.9265 | 4.0 | 3684 | 1.7687 | 41.6027 | 18.8083 | 34.8846 | 38.566 | 16.676 |
| 1.9176 | 5.0 | 4605 | 1.7651 | 41.6124 | 18.7668 | 35.0271 | 38.5305 | 16.6381 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for Vexemous/t5-small-finetuned-samsum
Base model
google-t5/t5-small