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nllb_b2b_checkpoints
yousrafourati/nllb_b2b_checkpoints
nllb_b2b_checkpoints is a machine learning model from yousrafourati. 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 cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- cc-by-nc-4.0
- Model type
- m2m_100
- Access
- Public
- Created
- Jun 6, 2026
- Updated
- Jun 6, 2026
- SHA
- aba6d3b0
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. -->
nllb_b2b_checkpoints
This model is a fine-tuned version of facebook/nllb-200-distilled-600M on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2663
- Bleu: 10.0040
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 5.6683 | 1.0 | 6 | 5.5640 | 4.2746 |
| 5.4244 | 2.0 | 12 | 4.3203 | 5.2153 |
| 4.0256 | 3.0 | 18 | 3.0693 | 8.8737 |
| 2.6780 | 4.0 | 24 | 2.4013 | 10.0040 |
| 1.7783 | 5.0 | 30 | 2.2663 | 10.0040 |
Framework versions
- Transformers 5.9.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Library
- transformers
- Type
- m2m_100
- License
- cc-by-nc-4.0
- Created
- Jun 6, 2026
- Updated
- Jun 6, 2026