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t5-small-finetuned-xsum
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1236
- Rouge1: 14.0749
- Rouge2: 4.3466
- Rougel: 14.0821
- Rougelsum: 14.0851
- Gen Len: 17.3883
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.1438 | 1.0 | 1833 | 0.1265 | 14.0996 | 4.3243 | 14.1043 | 14.1011 | 17.3871 |
| 0.1346 | 2.0 | 3666 | 0.1249 | 14.0652 | 4.348 | 14.0735 | 14.0794 | 17.3884 |
| 0.1343 | 3.0 | 5499 | 0.1236 | 14.0749 | 4.3466 | 14.0821 | 14.0851 | 17.3883 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0
- Datasets 2.14.5
- Tokenizers 0.14.1
