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mt5-translation
Kanstantsin/mt5-translation
mt5-translation is a machine learning model from Kanstantsin. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Mar 15, 2025
- Updated
- Mar 15, 2025
- SHA
- f8593926
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
mt5-translation
This model is a fine-tuned version of t5-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7159
- Bleu: 10.6499
- Gen Len: 16.7851
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 2.0268 | 1.0 | 2574 | 1.8408 | 9.2984 | 16.773 |
| 1.8847 | 2.0 | 5148 | 1.7699 | 10.0177 | 16.7833 |
| 1.8062 | 3.0 | 7722 | 1.7376 | 10.3779 | 16.7845 |
| 1.7531 | 4.0 | 10296 | 1.7196 | 10.6038 | 16.7847 |
| 1.7214 | 5.0 | 12870 | 1.7159 | 10.6499 | 16.7851 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.0
- Tokenizers 0.21.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Mar 15, 2025
- Updated
- Mar 15, 2025