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mt5-small-finetuned-bn_new
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: 2.9959
- Rouge1: {'precision': 15.65978835978838, 'recall': 10.193726027059379, 'fmeasure': 12.287113383501408}
- Rougel: {'precision': 14.951058201058215, 'recall': 9.73072853072855, 'fmeasure': 11.728911853731251}
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rougel |
|---|---|---|---|---|---|
| 8.555 | 1.0 | 253 | 2.9959 | {'precision': 15.65978835978838, 'recall': 10.193726027059379, 'fmeasure': 12.287113383501408} | {'precision': 14.951058201058215, 'recall': 9.73072853072855, 'fmeasure': 11.728911853731251} |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.0+cpu
- Datasets 2.10.1
- Tokenizers 0.12.1
