t5-small-finetuned-rahul-summariza
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7002
- Rouge1: 29.5043
- Rouge2: 23.832
- Rougel: 27.5786
- Rougelsum: 28.404
- Gen Len: 19.0
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: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.123 | 1.0 | 16 | 0.8258 | 27.2788 | 21.3634 | 25.7114 | 26.7324 | 19.0 |
| 0.9067 | 2.0 | 32 | 0.7539 | 28.873 | 23.5401 | 27.2337 | 27.939 | 19.0 |
| 0.8137 | 3.0 | 48 | 0.7280 | 29.1767 | 23.6599 | 27.7065 | 28.3569 | 19.0 |
| 0.7872 | 4.0 | 64 | 0.7230 | 29.0451 | 23.4597 | 27.2762 | 28.1324 | 19.0 |
| 0.7338 | 5.0 | 80 | 0.7133 | 29.4821 | 23.8113 | 27.4912 | 28.326 | 19.0 |
| 0.6913 | 6.0 | 96 | 0.7101 | 29.4237 | 23.8523 | 27.4109 | 28.2418 | 19.0 |
| 0.6679 | 7.0 | 112 | 0.7097 | 29.4237 | 23.8523 | 27.4109 | 28.2418 | 19.0 |
| 0.6963 | 8.0 | 128 | 0.7046 | 29.4237 | 23.8523 | 27.4109 | 28.2418 | 19.0 |
| 0.6223 | 9.0 | 144 | 0.7052 | 29.4237 | 23.7633 | 27.493 | 28.3362 | 19.0 |
| 0.6494 | 10.0 | 160 | 0.7019 | 29.4237 | 23.7633 | 27.493 | 28.3362 | 19.0 |
| 0.616 | 11.0 | 176 | 0.7010 | 29.4237 | 23.7633 | 27.493 | 28.3362 | 19.0 |
| 0.6058 | 12.0 | 192 | 0.7028 | 29.4237 | 23.7633 | 27.493 | 28.3362 | 19.0 |
| 0.5964 | 13.0 | 208 | 0.6996 | 29.4237 | 23.7633 | 27.493 | 28.3362 | 19.0 |
| 0.5958 | 14.0 | 224 | 0.6997 | 29.4237 | 23.7633 | 27.493 | 28.3362 | 19.0 |
| 0.57 | 15.0 | 240 | 0.6996 | 29.5043 | 23.832 | 27.5786 | 28.404 | 19.0 |
| 0.5714 | 16.0 | 256 | 0.6998 | 29.5043 | 23.832 | 27.5786 | 28.404 | 19.0 |
| 0.5648 | 17.0 | 272 | 0.6999 | 29.5043 | 23.832 | 27.5786 | 28.404 | 19.0 |
| 0.5258 | 18.0 | 288 | 0.7005 | 29.5043 | 23.832 | 27.5786 | 28.404 | 19.0 |
| 0.5692 | 19.0 | 304 | 0.7001 | 29.5043 | 23.832 | 27.5786 | 28.404 | 19.0 |
| 0.5708 | 20.0 | 320 | 0.7002 | 29.5043 | 23.832 | 27.5786 | 28.404 | 19.0 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2