t5-base-finetuned-qmsum
This model is a fine-tuned version of google-t5/t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.1567
- Rouge1: 28.3882
- Rouge2: 8.4191
- Rougel: 22.8604
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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|---|---|---|---|---|---|---|
| 3.5399 | 1.0 | 126 | 3.2929 | 27.9871 | 8.2442 | 23.2939 |
| 3.1401 | 2.0 | 252 | 3.2076 | 27.7588 | 7.6926 | 22.8498 |
| 2.9706 | 3.0 | 378 | 3.1678 | 28.9533 | 8.4516 | 23.4899 |
| 2.8244 | 4.0 | 504 | 3.1509 | 28.274 | 8.0721 | 22.897 |
| 2.7238 | 5.0 | 630 | 3.1472 | 27.9718 | 8.26 | 22.7717 |
| 2.6687 | 6.0 | 756 | 3.1513 | 28.3972 | 8.4436 | 22.9446 |
| 2.5844 | 7.0 | 882 | 3.1554 | 28.6233 | 8.5011 | 23.1638 |
| 2.5715 | 8.0 | 1008 | 3.1567 | 28.3882 | 8.4191 | 22.8604 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1