ukr-llama32-1b-qlora

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on the generator dataset. It achieves the following results on the evaluation set:

• Loss: 0.9021

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: 0.0002
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 62
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
0.889	0.32	1000	0.9420
0.9185	0.64	2000	0.9162
0.8283	0.96	3000	0.9021

Framework versions

• PEFT 0.15.1
• Transformers 4.47.1
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1