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m2m-diagnostica-automotive
Petr117/m2m-diagnostica-automotive
m2m-diagnostica-automotive is a machine learning model from Petr117. 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
- m2m_100
- Access
- Public
- Created
- Feb 28, 2026
- Updated
- Mar 3, 2026
- SHA
- 497be3a0
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. -->
m2m-diagnostica-automotive
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4527
- Bleu: 13.2
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: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 2.5320 | 1.0 | 283 | 0.5003 | 12.76 |
| 1.9859 | 2.0 | 566 | 0.4598 | 13.3 |
| 1.8792 | 3.0 | 849 | 0.4527 | 13.2 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu130
- Datasets 4.6.1
- Tokenizers 0.22.2
- Library
- transformers
- Type
- m2m_100
- Created
- Feb 28, 2026
- Updated
- Mar 3, 2026