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t5-small-finetuned-xsum
This model is a fine-tuned version of t5-small on the scitldr dataset. It achieves the following results on the evaluation set:
- Loss: 3.8686
- Rouge1: 24.7942
- Rouge2: 7.8227
- Rougel: 21.2018
- Rougelsum: 21.2779
- Gen Len: 18.4297
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: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 125 | 4.1327 | 23.5028 | 7.9229 | 19.2335 | 19.2839 | 18.5024 |
No log | 2.0 | 250 | 4.0197 | 23.4862 | 7.3941 | 19.1734 | 19.2273 | 18.4475 |
No log | 3.0 | 375 | 3.9659 | 24.0596 | 7.6225 | 20.2649 | 20.3197 | 18.2375 |
4.2188 | 4.0 | 500 | 3.9302 | 24.323 | 7.9627 | 20.7527 | 20.8616 | 18.1826 |
4.2188 | 5.0 | 625 | 3.9060 | 24.7138 | 7.9075 | 21.1786 | 21.2552 | 18.1939 |
4.2188 | 6.0 | 750 | 3.8900 | 24.696 | 7.7986 | 21.161 | 21.2083 | 18.2342 |
4.2188 | 7.0 | 875 | 3.8801 | 24.8363 | 7.852 | 21.2452 | 21.3039 | 18.3473 |
3.991 | 8.0 | 1000 | 3.8736 | 24.8537 | 7.9099 | 21.2259 | 21.3141 | 18.3845 |
3.991 | 9.0 | 1125 | 3.8700 | 24.7938 | 7.8088 | 21.1743 | 21.2603 | 18.4233 |
3.991 | 10.0 | 1250 | 3.8686 | 24.7942 | 7.8227 | 21.2018 | 21.2779 | 18.4297 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.12.1