Llama-3.1-8B-coding

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Llama-3.1-8B_tulu3_mixture_coding_full_ebs128_lr5e-06

This model is a fine-tuned version of meta-llama/Llama-3.1-8B on the tulu3_mixture_coding dataset. This checkpoint was released alongside https://arxiv.org/abs/2509.11167.

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-06
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 32
• total_train_batch_size: 128
• total_eval_batch_size: 16
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.03
• num_epochs: 1.0

Training results

Framework versions

• Transformers 4.51.1
• Pytorch 2.6.0+cu124
• Datasets 3.4.1
• Tokenizers 0.21.0