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en-vi-mbart50
thainq107/en-vi-mbart50
en-vi-mbart50 is a machine learning model from thainq107. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- mbart
- Access
- Public
- Created
- Feb 20, 2025
- Updated
- Feb 20, 2025
- SHA
- 2ec1ca3d
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. -->
en-vi-mabrt50
This model is a fine-tuned version of facebook/mbart-large-50-many-to-many-mmt on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2825
- Bleu: 34.6635
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: 3
Training results
| Training Loss | Epoch | Step | Bleu | Validation Loss |
|---|---|---|---|---|
| 1.228 | 0.2400 | 1000 | 33.4010 | 1.3419 |
| 1.2022 | 0.4800 | 2000 | 34.0752 | 1.3063 |
| 1.1771 | 0.7199 | 3000 | 34.1612 | 1.2806 |
| 1.1607 | 0.9599 | 4000 | 34.3856 | 1.2582 |
| 0.9698 | 1.1999 | 5000 | 34.3075 | 1.2860 |
| 0.9298 | 1.4399 | 6000 | 34.4419 | 1.2671 |
| 0.9282 | 1.6799 | 7000 | 34.7962 | 1.2552 |
| 0.9174 | 1.9198 | 8000 | 34.7904 | 1.2516 |
| 0.8538 | 2.1598 | 9000 | 1.3000 | 34.3462 |
| 0.822 | 2.3998 | 10000 | 1.2953 | 34.3928 |
| 0.8206 | 2.6398 | 11000 | 1.2834 | 34.4372 |
| 0.8177 | 2.8798 | 12000 | 1.2825 | 34.6635 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 2.20.0
- Tokenizers 0.21.0
- Library
- transformers
- Type
- mbart
- Created
- Feb 20, 2025
- Updated
- Feb 20, 2025