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: 3.2159
- Rouge1: 17.3504
- Rouge2: 8.219
- Rougel: 16.7598
- Rougelsum: 16.9027
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 |
|---|---|---|---|---|---|---|---|
| 5.8554 | 1.0 | 1541 | 3.4109 | 14.0843 | 7.0483 | 13.7876 | 13.7424 |
| 3.5936 | 2.0 | 3082 | 3.3110 | 16.9351 | 8.9452 | 16.1951 | 16.2707 |
| 3.2943 | 3.0 | 4623 | 3.2440 | 18.9749 | 10.2572 | 18.3207 | 18.3447 |
| 3.1378 | 4.0 | 6164 | 3.2157 | 17.5435 | 9.5501 | 16.976 | 16.9846 |
| 3.0374 | 5.0 | 7705 | 3.2017 | 17.2499 | 8.6003 | 16.8574 | 16.8485 |
| 2.9644 | 6.0 | 9246 | 3.1948 | 16.7856 | 7.7093 | 16.3617 | 16.4731 |
| 2.921 | 7.0 | 10787 | 3.2160 | 18.1708 | 8.8001 | 17.4812 | 17.5949 |
| 2.8907 | 8.0 | 12328 | 3.2159 | 17.3504 | 8.219 | 16.7598 | 16.9027 |
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