llama-3.2-3b-qlora-alpaca_r64

<!-- 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. -->

llama-3.2-3b-qlora-alpaca_r64

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

• Loss: 0.0566

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: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Framework versions

• PEFT 0.19.1
• Transformers 5.8.1
• Pytorch 2.12.0+cu130
• Datasets 4.8.5
• Tokenizers 0.22.2