t5-small-govReport-boardpapers-3072
This model is a fine-tuned version of RMWeerasinghe/t5-small-finetuned-govReport-3072 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.6701
- Rouge1: 0.0443
- Rouge2: 0.0194
- Rougel: 0.0382
- Rougelsum: 0.0443
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: 4e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| No log | 0.67 | 1 | 3.9496 | 0.0584 | 0.0214 | 0.0482 | 0.0572 |
| No log | 2.0 | 3 | 3.9252 | 0.0562 | 0.0223 | 0.0463 | 0.0562 |
| No log | 2.67 | 4 | 3.9121 | 0.0597 | 0.0223 | 0.0485 | 0.0596 |
| No log | 4.0 | 6 | 3.8880 | 0.0597 | 0.0223 | 0.0485 | 0.0596 |
| No log | 4.67 | 7 | 3.8755 | 0.0597 | 0.0223 | 0.0485 | 0.0596 |
| No log | 6.0 | 9 | 3.8506 | 0.0597 | 0.0223 | 0.0485 | 0.0596 |
| No log | 6.67 | 10 | 3.8395 | 0.0553 | 0.0197 | 0.0441 | 0.0541 |
| No log | 8.0 | 12 | 3.8172 | 0.0582 | 0.0262 | 0.049 | 0.057 |
| No log | 8.67 | 13 | 3.8065 | 0.0582 | 0.0262 | 0.049 | 0.057 |
| No log | 10.0 | 15 | 3.7862 | 0.0582 | 0.0257 | 0.049 | 0.057 |
| No log | 10.67 | 16 | 3.7769 | 0.057 | 0.0262 | 0.049 | 0.0556 |
| No log | 12.0 | 18 | 3.7599 | 0.0577 | 0.0294 | 0.0495 | 0.0575 |
| No log | 12.67 | 19 | 3.7522 | 0.0487 | 0.0174 | 0.042 | 0.0474 |
| 4.3528 | 14.0 | 21 | 3.7378 | 0.048 | 0.0155 | 0.0406 | 0.0461 |
| 4.3528 | 14.67 | 22 | 3.7310 | 0.0536 | 0.0206 | 0.0421 | 0.0511 |
| 4.3528 | 16.0 | 24 | 3.7187 | 0.048 | 0.017 | 0.0394 | 0.0448 |
| 4.3528 | 16.67 | 25 | 3.7132 | 0.043 | 0.017 | 0.0374 | 0.041 |
| 4.3528 | 18.0 | 27 | 3.7031 | 0.043 | 0.017 | 0.0374 | 0.041 |
| 4.3528 | 18.67 | 28 | 3.6985 | 0.043 | 0.017 | 0.0374 | 0.041 |
| 4.3528 | 20.0 | 30 | 3.6905 | 0.043 | 0.017 | 0.0374 | 0.041 |
| 4.3528 | 20.67 | 31 | 3.6869 | 0.043 | 0.017 | 0.0374 | 0.041 |
| 4.3528 | 22.0 | 33 | 3.6807 | 0.0442 | 0.0194 | 0.0381 | 0.0423 |
| 4.3528 | 22.67 | 34 | 3.6781 | 0.0442 | 0.0194 | 0.0381 | 0.0423 |
| 4.3528 | 24.0 | 36 | 3.6740 | 0.0442 | 0.0194 | 0.0381 | 0.0423 |
| 4.3528 | 24.67 | 37 | 3.6725 | 0.0442 | 0.0194 | 0.0381 | 0.0423 |
| 4.3528 | 26.0 | 39 | 3.6705 | 0.0443 | 0.0194 | 0.0382 | 0.0443 |
| 4.0602 | 26.67 | 40 | 3.6701 | 0.0443 | 0.0194 | 0.0382 | 0.0443 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.15.1