t5-small-finetuned-dialogsum-v3
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2045
- Rouge1: 38.3615
- Rouge2: 16.0241
- Rougel: 32.901
- Rougelsum: 34.8687
- Gen Len: 18.892
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: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.7344 | 1.0 | 779 | 1.4251 | 33.4125 | 10.7502 | 28.0588 | 30.0903 | 18.858 |
| 1.4975 | 2.0 | 1558 | 1.3623 | 34.4069 | 11.9728 | 29.0576 | 31.156 | 18.874 |
| 1.4621 | 3.0 | 2337 | 1.3355 | 34.9786 | 12.314 | 29.4869 | 31.4407 | 18.86 |
| 1.4149 | 4.0 | 3116 | 1.3119 | 35.5881 | 12.9123 | 30.1883 | 32.0652 | 18.874 |
| 1.4009 | 5.0 | 3895 | 1.2905 | 36.3104 | 13.8382 | 30.893 | 32.7095 | 18.882 |
| 1.3709 | 6.0 | 4674 | 1.2736 | 36.3456 | 13.8426 | 30.7526 | 32.6784 | 18.906 |
| 1.3589 | 7.0 | 5453 | 1.2671 | 36.6543 | 14.2334 | 30.98 | 32.9241 | 18.892 |
| 1.3373 | 8.0 | 6232 | 1.2557 | 37.2264 | 14.7072 | 31.413 | 33.2844 | 18.914 |
| 1.3168 | 9.0 | 7011 | 1.2520 | 37.315 | 14.8744 | 31.6711 | 33.4863 | 18.862 |
| 1.3044 | 10.0 | 7790 | 1.2454 | 37.8787 | 15.4762 | 32.3244 | 34.107 | 18.886 |
| 1.2915 | 11.0 | 8569 | 1.2380 | 38.0242 | 15.5379 | 32.4465 | 34.292 | 18.862 |
| 1.2926 | 12.0 | 9348 | 1.2362 | 37.82 | 15.4074 | 32.0479 | 33.9622 | 18.882 |
| 1.2818 | 13.0 | 10127 | 1.2318 | 38.2168 | 16.0879 | 32.592 | 34.5757 | 18.892 |
| 1.2766 | 14.0 | 10906 | 1.2257 | 38.559 | 16.2997 | 32.9956 | 34.9149 | 18.864 |
| 1.2666 | 15.0 | 11685 | 1.2245 | 38.1764 | 15.9612 | 32.525 | 34.6476 | 18.878 |
| 1.2602 | 16.0 | 12464 | 1.2191 | 38.3852 | 16.085 | 32.809 | 34.7302 | 18.884 |
| 1.2523 | 17.0 | 13243 | 1.2164 | 38.426 | 16.1149 | 32.6806 | 34.7701 | 18.894 |
| 1.2466 | 18.0 | 14022 | 1.2142 | 38.6658 | 16.0599 | 32.9194 | 34.905 | 18.89 |
| 1.2332 | 19.0 | 14801 | 1.2152 | 38.4253 | 15.9033 | 32.7993 | 34.8635 | 18.896 |
| 1.2344 | 20.0 | 15580 | 1.2093 | 38.6261 | 16.0519 | 33.1192 | 34.9215 | 18.918 |
| 1.2278 | 21.0 | 16359 | 1.2091 | 38.6618 | 16.2012 | 33.134 | 35.0842 | 18.904 |
| 1.2255 | 22.0 | 17138 | 1.2077 | 38.6482 | 16.142 | 33.0472 | 35.037 | 18.906 |
| 1.2305 | 23.0 | 17917 | 1.2068 | 38.6584 | 16.1184 | 32.9757 | 34.9885 | 18.89 |
| 1.2275 | 24.0 | 18696 | 1.2069 | 38.3795 | 16.0471 | 32.9456 | 34.8267 | 18.874 |
| 1.2227 | 25.0 | 19475 | 1.2064 | 38.4788 | 16.1603 | 33.0022 | 34.8844 | 18.87 |
| 1.218 | 26.0 | 20254 | 1.2051 | 38.5133 | 16.0813 | 33.0334 | 34.9492 | 18.89 |
| 1.2183 | 27.0 | 21033 | 1.2046 | 38.3323 | 15.839 | 32.7421 | 34.7147 | 18.884 |
| 1.2195 | 28.0 | 21812 | 1.2040 | 38.3573 | 16.0328 | 32.86 | 34.8107 | 18.892 |
| 1.2145 | 29.0 | 22591 | 1.2045 | 38.3932 | 16.1115 | 32.9154 | 34.8664 | 18.894 |
| 1.212 | 30.0 | 23370 | 1.2045 | 38.3615 | 16.0241 | 32.901 | 34.8687 | 18.892 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1