t5-small-finetuned-xsum-custom
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5478
- Rouge1: 28.4804
- Rouge2: 7.7367
- Rougel: 22.7607
- Rougelsum: 22.762
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: 4e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.9745 | 1.0 | 999 | 2.6463 | 25.8883 | 6.5128 | 20.4979 | 20.4769 |
| 2.7924 | 2.0 | 1998 | 2.5992 | 27.3518 | 7.3916 | 21.7638 | 21.7476 |
| 2.7061 | 3.0 | 2997 | 2.5763 | 27.7159 | 7.5086 | 22.188 | 22.1916 |
| 2.6502 | 4.0 | 3996 | 2.5637 | 28.175 | 7.7661 | 22.6274 | 22.6179 |
| 2.6044 | 5.0 | 4995 | 2.5571 | 28.2348 | 7.7937 | 22.6196 | 22.6568 |
| 2.5781 | 6.0 | 5994 | 2.5526 | 28.319 | 7.7453 | 22.6005 | 22.6044 |
| 2.5618 | 7.0 | 6993 | 2.5488 | 28.4962 | 7.7803 | 22.7827 | 22.803 |
| 2.5441 | 8.0 | 7992 | 2.5478 | 28.4804 | 7.7367 | 22.7607 | 22.762 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1