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kaggle-competitionV4
AjithBharadwaj/kaggle-competitionV4
kaggle-competitionV4 is a machine learning model from AjithBharadwaj. 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
- Feb 15, 2026
- Updated
- Feb 16, 2026
- SHA
- cb2191d2
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. -->
kaggle-competitionV4
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: 1.4491
- Score: 33.5067
- Bleu: 25.3096
- Chrf: 44.3587
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
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Score | Bleu | Chrf |
|---|---|---|---|---|---|---|
| No log | 0.5445 | 300 | 2.1560 | 19.4321 | 12.1497 | 31.0796 |
| 2.5006 | 1.0889 | 600 | 1.8783 | 24.8743 | 17.1755 | 36.0241 |
| 2.5006 | 1.6334 | 900 | 1.7428 | 27.3208 | 19.4256 | 38.4248 |
| 1.8822 | 2.1779 | 1200 | 1.6604 | 29.1509 | 21.0993 | 40.2751 |
| 1.6935 | 2.7223 | 1500 | 1.5974 | 29.3307 | 20.8970 | 41.1681 |
| 1.6935 | 3.2668 | 1800 | 1.5557 | 31.1230 | 22.9892 | 42.1347 |
| 1.5797 | 3.8113 | 2100 | 1.5209 | 30.8637 | 22.3684 | 42.5854 |
| 1.5797 | 4.3557 | 2400 | 1.4980 | 32.1591 | 23.8574 | 43.3495 |
| 1.5044 | 4.9002 | 2700 | 1.4774 | 32.6654 | 24.3790 | 43.7686 |
| 1.4484 | 5.4446 | 3000 | 1.4651 | 33.2768 | 25.0795 | 44.1535 |
| 1.4484 | 5.9891 | 3300 | 1.4541 | 32.7798 | 24.3589 | 44.1118 |
| 1.4135 | 6.5336 | 3600 | 1.4491 | 33.5067 | 25.3096 | 44.3587 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.2
- Tokenizers 0.22.1
- Library
- transformers
- Type
- m2m_100
- License
- cc-by-nc-4.0
- Created
- Feb 15, 2026
- Updated
- Feb 16, 2026