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Magpie-Align/MagpieLM-4B-SFT-v0.1

sourceHugging Faceupdated 2y agoView on Hugging Face
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Magpie

<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>

🐦 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
  • —trainbatchsize: 1
  • —evalbatchsize: 1
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 4
  • —gradientaccumulationsteps: 32
  • —totaltrainbatch_size: 128
  • —totalevalbatch_size: 4
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 51
  • —num_epochs: 2

Training results

Training LossEpochStepValidation Loss
1.10260.003811.1547
0.69940.2015530.7142
0.61810.40301060.6375
0.59670.60451590.6134
0.57930.80602120.6004
0.57361.00752650.5914
0.54111.19383180.5883
0.54021.39533710.5864
0.54231.59684240.5856
0.54081.79834770.5854

Framework versions

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

<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/> <details><summary>See axolotl config</summary>

axolotl version: 0.4.1

yaml
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>