t5-base-snl
This model is a fine-tuned version of north/t5_base_NCC_lm on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.0574
- Rouge1: 29.7694
- Rouge2: 15.6776
- Rougel: 27.3556
- Rougelsum: 28.4819
- 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.9943 | 1.0 | 170 | 2.2042 | 28.1135 | 13.7477 | 25.4842 | 26.6467 | 18.9768 |
| 2.7955 | 2.0 | 340 | 2.1561 | 28.5159 | 14.3492 | 26.0596 | 27.2431 | 18.9853 |
| 2.6378 | 3.0 | 510 | 2.1310 | 28.9554 | 14.6901 | 26.4208 | 27.5523 | 18.9915 |
| 2.5962 | 4.0 | 680 | 2.1110 | 29.381 | 15.1503 | 26.8406 | 27.9653 | 18.9915 |
| 2.5369 | 5.0 | 850 | 2.1020 | 29.5767 | 15.2692 | 27.0113 | 28.1849 | 18.9963 |
| 2.5103 | 6.0 | 1020 | 2.0907 | 29.6354 | 15.434 | 27.0893 | 28.2703 | 18.9963 |
| 2.4524 | 7.0 | 1190 | 2.0840 | 29.7812 | 15.4963 | 27.2779 | 28.385 | 18.9963 |
| 2.4472 | 8.0 | 1360 | 2.0800 | 29.6011 | 15.5138 | 27.1381 | 28.2799 | 18.9963 |
| 2.4089 | 9.0 | 1530 | 2.0752 | 29.7647 | 15.6183 | 27.318 | 28.4747 | 18.9963 |
| 2.4011 | 10.0 | 1700 | 2.0710 | 29.6533 | 15.5536 | 27.2687 | 28.4457 | 19.0 |
| 2.3792 | 11.0 | 1870 | 2.0656 | 29.8668 | 15.6931 | 27.4208 | 28.5477 | 19.0 |
| 2.3588 | 12.0 | 2040 | 2.0635 | 29.8378 | 15.682 | 27.4635 | 28.5803 | 18.9963 |
| 2.3397 | 13.0 | 2210 | 2.0630 | 29.9043 | 15.7535 | 27.5065 | 28.6539 | 19.0 |
| 2.3201 | 14.0 | 2380 | 2.0600 | 29.7926 | 15.7077 | 27.4066 | 28.5302 | 18.9963 |
| 2.3241 | 15.0 | 2550 | 2.0615 | 29.8536 | 15.7929 | 27.4572 | 28.5704 | 19.0 |
| 2.3183 | 16.0 | 2720 | 2.0574 | 29.7529 | 15.6729 | 27.3388 | 28.4678 | 19.0 |
| 2.3346 | 17.0 | 2890 | 2.0571 | 29.7443 | 15.6459 | 27.3245 | 28.4549 | 19.0 |
| 2.2932 | 18.0 | 3060 | 2.0577 | 29.7467 | 15.6717 | 27.3391 | 28.4541 | 19.0 |
| 2.2755 | 19.0 | 3230 | 2.0574 | 29.7694 | 15.6776 | 27.3556 | 28.4819 | 19.0 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2