llama-3-86-lora-pretrain

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the sm_artile dataset. It achieves the following results on the evaluation set:

• Loss: 2.2129

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: 0.0001
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 200
• num_epochs: 3.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
2.2949	0.6369	500	2.3349
2.2907	1.2739	1000	2.2571
2.0957	1.9108	1500	2.2253
2.2352	2.5478	2000	2.2145

Framework versions

• PEFT 0.10.0
• Transformers 4.40.0
• Pytorch 2.2.2+cu121
• Datasets 2.18.0
• Tokenizers 0.19.1