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vinai_v2_meddict_meddictgem
Bmingg/vinai_v2_meddict_meddictgem
vinai_v2_meddict_meddictgem is a machine learning model from Bmingg. 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 agpl-3.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- agpl-3.0
- Model type
- mbart
- Access
- Public
- Created
- Oct 4, 2025
- Updated
- Oct 5, 2025
- SHA
- cca108cb
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. -->
vinai_v2_meddict_meddictgem
This model is a fine-tuned version of vinai/vinai-translate-en2vi-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2746
- Bleu: 55.4266
- Gen Len: 43.4087
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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 0.5713 | 1.0 | 1004 | 0.8669 | 54.3335 | 43.3722 |
| 0.31 | 2.0 | 2008 | 0.9003 | 54.1622 | 44.4467 |
| 0.1771 | 3.0 | 3012 | 0.9956 | 55.4098 | 43.2584 |
| 0.1306 | 4.0 | 4016 | 1.1531 | 55.6861 | 43.1188 |
| 0.1361 | 5.0 | 5020 | 1.2746 | 55.4266 | 43.4087 |
Framework versions
- Transformers 4.54.0.dev0
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
- Library
- transformers
- Type
- mbart
- License
- agpl-3.0
- Created
- Oct 4, 2025
- Updated
- Oct 5, 2025