t5-small-finetuned-t5-summarization
This model is a fine-tuned version of t5-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:
- Loss: 1.7613
- Rouge1: 24.5755
- Rouge2: 11.8424
- Rougel: 20.3031
- Rougelsum: 23.1867
- Gen Len: 18.9999
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: 6e-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: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.9891 | 1.0 | 17945 | 1.7981 | 24.382 | 11.7099 | 20.1707 | 23.0021 | 18.9998 |
| 1.9527 | 2.0 | 35890 | 1.7816 | 24.4884 | 11.7673 | 20.2698 | 23.1233 | 19.0 |
| 1.9421 | 3.0 | 53835 | 1.7728 | 24.5782 | 11.8401 | 20.3343 | 23.2033 | 18.9997 |
| 1.9298 | 4.0 | 71780 | 1.7677 | 24.566 | 11.8723 | 20.3296 | 23.1943 | 18.9999 |
| 1.9256 | 5.0 | 89725 | 1.7619 | 24.5662 | 11.8385 | 20.3265 | 23.2016 | 18.9999 |
| 1.9056 | 6.0 | 107670 | 1.7613 | 24.5755 | 11.8424 | 20.3031 | 23.1867 | 18.9999 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2