Llama-3.2-3B-Instruct_sft_sg_values

This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the sft_sg_values dataset. It achieves the following results on the evaluation set:

• Loss: 0.2716

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: 1e-06
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• total_eval_batch_size: 4
• optimizer: Use OptimizerNames.ADAMW_TORCH 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: 0.1
• num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.3937	0.3738	250	0.3563
0.2652	0.7477	500	0.2791

Framework versions

• PEFT 0.15.2
• Transformers 4.51.1
• Pytorch 2.6.0+cu124
• Datasets 2.21.0
• Tokenizers 0.21.1