long_t5
This model is a fine-tuned version of google/long-t5-tglobal-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5158
- Rouge1: 0.5214
- Rouge2: 0.3347
- Rougel: 0.4751
- Rougelsum: 0.4746
- Gen Len: 25.9513
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: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.232 | 1.0 | 1600 | 1.6810 | 0.4704 | 0.2861 | 0.4256 | 0.4251 | 26.6112 |
| 2.0229 | 2.0 | 3200 | 1.6167 | 0.4859 | 0.2991 | 0.4412 | 0.4407 | 26.1006 |
| 1.9239 | 3.0 | 4800 | 1.5805 | 0.4924 | 0.3049 | 0.4475 | 0.4468 | 26.8169 |
| 1.8454 | 4.0 | 6400 | 1.5669 | 0.4968 | 0.3093 | 0.4517 | 0.4511 | 25.925 |
| 1.7626 | 5.0 | 8000 | 1.5432 | 0.4973 | 0.3132 | 0.453 | 0.4525 | 26.4362 |
| 1.6995 | 6.0 | 9600 | 1.5352 | 0.5045 | 0.3188 | 0.4596 | 0.459 | 26.1219 |
| 1.682 | 7.0 | 11200 | 1.5255 | 0.5066 | 0.3198 | 0.4613 | 0.4609 | 26.1581 |
| 1.6286 | 8.0 | 12800 | 1.5210 | 0.5113 | 0.3245 | 0.4663 | 0.466 | 26.1725 |
| 1.593 | 9.0 | 14400 | 1.5195 | 0.5102 | 0.3235 | 0.464 | 0.4638 | 25.8944 |
| 1.5784 | 10.0 | 16000 | 1.5166 | 0.5133 | 0.3265 | 0.4665 | 0.4661 | 25.685 |
| 1.5615 | 11.0 | 17600 | 1.5135 | 0.5161 | 0.3284 | 0.47 | 0.4695 | 25.8681 |
| 1.5391 | 12.0 | 19200 | 1.5106 | 0.5156 | 0.3303 | 0.4703 | 0.4701 | 26.1781 |
| 1.5077 | 13.0 | 20800 | 1.5095 | 0.5177 | 0.3317 | 0.4724 | 0.4721 | 26.0456 |
| 1.4923 | 14.0 | 22400 | 1.5163 | 0.5185 | 0.3321 | 0.4728 | 0.4723 | 26.17 |
| 1.4545 | 15.0 | 24000 | 1.5128 | 0.5181 | 0.3337 | 0.4727 | 0.4724 | 25.8219 |
| 1.4489 | 16.0 | 25600 | 1.5135 | 0.5209 | 0.3349 | 0.4744 | 0.4743 | 26.0369 |
| 1.4481 | 17.0 | 27200 | 1.5153 | 0.5218 | 0.3349 | 0.4751 | 0.4748 | 26.1744 |
| 1.4287 | 18.0 | 28800 | 1.5134 | 0.521 | 0.335 | 0.4752 | 0.4747 | 25.9525 |
| 1.389 | 19.0 | 30400 | 1.5155 | 0.5212 | 0.3348 | 0.4756 | 0.4751 | 26.0369 |
| 1.4215 | 20.0 | 32000 | 1.5158 | 0.5214 | 0.3347 | 0.4751 | 0.4746 | 25.9513 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1