t5-small-finetuned-qmsum
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.4617
- Rouge1: 27.6423
- Rouge2: 8.5163
- Rougel: 23.1505
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 |
|---|---|---|---|---|---|---|
| 3.3956 | 1.0 | 126 | 3.5354 | 27.6519 | 8.0746 | 23.1321 |
| 3.407 | 2.0 | 252 | 3.5115 | 27.4959 | 8.1111 | 23.1004 |
| 3.36 | 3.0 | 378 | 3.4898 | 27.7611 | 8.3366 | 23.1863 |
| 3.3032 | 4.0 | 504 | 3.4804 | 27.5676 | 8.2376 | 23.1387 |
| 3.2602 | 5.0 | 630 | 3.4727 | 28.1638 | 8.6819 | 23.4878 |
| 3.258 | 6.0 | 756 | 3.4644 | 27.8802 | 8.5634 | 23.3815 |
| 3.2167 | 7.0 | 882 | 3.4626 | 27.649 | 8.5533 | 23.2101 |
| 3.203 | 8.0 | 1008 | 3.4617 | 27.6423 | 8.5163 | 23.1505 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for ecat3rina/t5-small-finetuned-qmsum
Base model
google-t5/t5-small