Final_Model

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

• Loss: 0.8592

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: 3e-05
• train_batch_size: 1
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 8
• 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_steps: 50
• num_epochs: 6
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.9709	0.9995	231	0.9373
0.9107	1.9989	462	0.8998
0.8754	2.9984	693	0.8803
0.8334	3.9978	924	0.8679
0.8159	4.9973	1155	0.8614
0.8283	5.9968	1386	0.8592

Framework versions

• PEFT 0.13.2
• Transformers 4.46.2
• Pytorch 2.0.1+cu117
• Datasets 3.1.0
• Tokenizers 0.20.3