Llama-3-8B-ARC-Challenge-10-19-LoRA-train-A

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

• Loss: 1.4134

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: 5e-05
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
1.7207	1.0	140	1.4934
1.4082	2.0	280	1.4199
1.4326	3.0	420	1.4134

Framework versions

• PEFT 0.11.1
• Transformers 4.41.1
• Pytorch 2.3.1
• Datasets 2.19.1
• Tokenizers 0.19.1