EvolCodeLlama-3.1-8B-Instruct

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct using QLoRA (4-bit precision) on the mlabonne/Evol-Instruct-Python-1k dataset. It achieves the following results on the evaluation set:

• Loss: 0.4057

Training:

It was trained on an A40 for more than 1 hour using Axolotl.

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0002
• train_batch_size: 2
• eval_batch_size: 2
• 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_steps: 100
• num_epochs: 3

The lose curves are as:

Framework versions

• PEFT 0.12.0
• Transformers 4.44.0
• Pytorch 2.4.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1