t5-small-finetuned-webnlg-mt-2.0e-04
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Gen Len: 43.5977
- Loss: 0.3487
- Rouge1: 0.8216
- Rouge2: 0.6463
- Rougel: 0.7033
- Rougelsum: 0.7274
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: 0.0002
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Gen Len | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|---|
| 0.604 | 1.4 | 1500 | 43.3072 | 0.4256 | 0.7894 | 0.6008 | 0.6683 | 0.6931 |
| 0.4922 | 2.79 | 3000 | 43.8020 | 0.3684 | 0.8144 | 0.6352 | 0.6928 | 0.7170 |
| 0.4474 | 4.19 | 4500 | 43.5977 | 0.3487 | 0.8216 | 0.6463 | 0.7033 | 0.7274 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3