mt5-destination-inference
This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.0350
- Rouge1: 4.0
- Rouge2: 0.0
- Rougel: 4.0
- Rougelsum: 4.0
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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 20.4559 | 1.0 | 250 | 9.7574 | 0.0 | 0.0 | 0.0 | 0.0 |
| 9.5672 | 2.0 | 500 | 4.8087 | 0.0 | 0.0 | 0.0 | 0.0 |
| 6.3205 | 3.0 | 750 | 3.9127 | 0.2 | 0.0 | 0.2 | 0.2 |
| 5.3432 | 4.0 | 1000 | 3.5081 | 1.4 | 0.0 | 1.4 | 1.4 |
| 4.9042 | 5.0 | 1250 | 3.3167 | 2.2 | 0.0 | 2.2 | 2.2 |
| 4.6882 | 6.0 | 1500 | 3.1341 | 3.2 | 0.0 | 3.2 | 3.2 |
| 4.538 | 7.0 | 1750 | 3.0736 | 4.0 | 0.0 | 4.0 | 4.0 |
| 4.4857 | 8.0 | 2000 | 3.0350 | 4.0 | 0.0 | 4.0 | 4.0 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3