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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: Qwen/Qwen3-4B-Base |
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tags: |
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- llm |
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- indic |
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model-index: |
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- name: Hex-1 |
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results: [] |
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language: |
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- hi |
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- te |
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- ta |
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- ml |
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- kn |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Hex-1 |
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Hex-1 is a 4-billion parameter language model specifically optimized for Indian languages. It supports five major Indian languages, including Hindi, Kannada, Telugu, Tamil and Malayalam. |
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When benchmarked against leading models like Gemma-2B, LLaMA-3.2-3B, and Sarvam-1, Hex1 delivers best-in-class performance in all five supported languages on MMLU dataset. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 7 |
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- total_train_batch_size: 56 |
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- total_eval_batch_size: 56 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3.0 |
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### Training results - Multilingual Task Performance Comparison |
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| Language | Hellaswag | ARC-c | ARC-e | MMLU | BoolQ | |
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|------------|-----------|--------|--------|--------|--------| |
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| Hindi | 47.85 | 36.68 | 52.14 | 46.73 | 57.61 | |
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| Tamil | 49.45 | 38.65 | 53.45 | 44.71 | 45.87 | |
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| Telugu | 50.84 | 37.96 | 53.36 | 46.85 | 51.89 | |
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| Kannada | 52.16 | 38.31 | 53.11 | 46.38 | 52.32 | |
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| Malayalam | 46.32 | 29.60 | 40.86 | 43.63 | 46.69 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.7.0+cu126 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
