mt5-small-finetuned-amazon-en-es
This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.0150
- Rouge1: 16.6244
- Rouge2: 7.4737
- Rougel: 16.2514
- Rougelsum: 16.3475
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 3.3536 | 1.0 | 1209 | 3.1069 | 17.673 | 8.5372 | 17.1607 | 17.1184 |
| 3.3641 | 2.0 | 2418 | 3.0533 | 17.2312 | 8.728 | 16.7626 | 16.7101 |
| 3.2384 | 3.0 | 3627 | 3.0481 | 15.9593 | 7.8483 | 15.7221 | 15.8227 |
| 3.1555 | 4.0 | 4836 | 3.0504 | 16.3465 | 7.9873 | 15.9367 | 15.9714 |
| 3.0826 | 5.0 | 6045 | 3.0267 | 16.285 | 7.4032 | 15.7749 | 15.8915 |
| 3.0396 | 6.0 | 7254 | 3.0217 | 16.5194 | 7.6637 | 16.1961 | 16.214 |
| 3.0181 | 7.0 | 8463 | 3.0122 | 16.068 | 7.2738 | 15.7885 | 15.8982 |
| 2.9965 | 8.0 | 9672 | 3.0150 | 16.6244 | 7.4737 | 16.2514 | 16.3475 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
google/mt5-small