MagpieLM-4B-SFT-v0.1

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🐦 MagpieLM-4B-SFT-v0.1

Project Web: https://magpie-align.github.io/

Arxiv Technical Report: https://arxiv.org/abs/2406.08464

Codes: https://github.com/magpie-align/magpie

About This Model

Model full name: Llama3.1-MagpieLM-4B-SFT-v0.1

This model is a fine-tuned version of nvidia/Llama-3.1-Minitron-4B-Width-Base on Magpie-Align/MagpieLM-SFT-Data-v0.1 dataset.

This is the intermediate checkpoint for fine-tuning Magpie-Align/MagpieLM-4B-Chat-v0.1.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 32
• total_train_batch_size: 128
• total_eval_batch_size: 4
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 51
• num_epochs: 2

Training results

Framework versions

• Transformers 4.45.0.dev0
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1

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<details><summary>See axolotl config</summary>

axolotl version: 0.4.1

base_model: nvidia/Llama-3.1-Minitron-4B-Width-Base
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
chat_template: llama3

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: Magpie-Align/MagpieLM-SFT-Data-v0.1
    type: sharegpt
    conversation: llama3
dataset_prepared_path: last_run_prepared
val_set_size: 0.001
output_dir: axolotl_out/MagpieLM-4B-SFT-v0.1

sequence_len: 8192
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true

wandb_project: SynDa
wandb_entity:
wandb_watch:
wandb_name: Llama3.1-MagpieLM-4B-SFT-v0.1
wandb_log_model:
hub_model_id: Magpie-Align/MagpieLM-4B-SFT-v0.1

gradient_accumulation_steps: 32
micro_batch_size: 1
num_epochs: 2
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 2e-5

train_on_inputs: false
group_by_length: false
bf16: true
fp16:
tf32: false

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_ratio: 0.1
evals_per_epoch: 5
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  pad_token: <|end_of_text|>

</details><br>