metadata
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-3B-Instruct
tags:
- generated_from_trainer
datasets:
- demoversion/cf-cpp-to-python-code-generation
model-index:
- name: outputs/cf-llm-finetune-llama-3.2-3b-lora
results: []
See axolotl config
axolotl version: 0.10.0
base_model: meta-llama/Llama-3.2-3B-Instruct
load_in_8bit: true
load_in_4bit: false
datasets:
- path: ./data/train_openai_response_transformed.jsonl
type: chat_template
field_messages: messages
message_property_mappings:
role: role
content: content
val_file: ./data/val_openai_response_transformed.jsonl
val_set_size: 0.0
output_dir: ./outputs/cf-llm-finetune-llama-3.2-3b-lora
adapter: lora
lora_model_dir:
sequence_len: 4096
sample_packing: false
eval_sample_packing: true
pad_to_sequence_len: true
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
bf16: auto
tf32: false
gradient_checkpointing: true
resume_from_checkpoint:
logging_steps: 1
flash_attention: false
warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
weight_decay: 0.0
special_tokens:
pad_token: "<|end_of_text|>"
outputs/cf-llm-finetune-llama-3.2-3b-lora
This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the ./data/train_openai_response_transformed.jsonl dataset.
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- training_steps: 688
Training results
Framework versions
- PEFT 0.15.2
- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2