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m2m100-7E5-6E-1
wandererupak/m2m100-7E5-6E-1
m2m100-7E5-6E-1 is a machine learning model from wandererupak. 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 mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- m2m_100
- Access
- Public
- Created
- Sep 27, 2025
- Updated
- Sep 27, 2025
- SHA
- 078a27e7
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. -->
m2m100-7E5-6E-1
This model is a fine-tuned version of facebook/m2m100_418M on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1977
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: 7e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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_ratio: 0.06
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2598 | 1.0 | 3001 | 0.2628 |
| 0.1844 | 2.0 | 6002 | 0.2177 |
| 0.1284 | 3.0 | 9003 | 0.2031 |
| 0.0872 | 4.0 | 12004 | 0.1953 |
| 0.0533 | 5.0 | 15005 | 0.1953 |
| 0.0315 | 6.0 | 18006 | 0.1977 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.1.1
- Tokenizers 0.22.0
- Library
- transformers
- Type
- m2m_100
- License
- mit
- Created
- Sep 27, 2025
- Updated
- Sep 27, 2025