Model Visualization

Hamanasu 15B R2 PT

🌌 Overview

This is the 2nd pretrain of Phi-4 Continued from the Orginal Asstr-Erebus Pretrain. This pretrain used 500 million tokens from

  • NewEden/Orion-LIT

This model has not been instruct tuned, Ablities to converse may be reduced from the original model, If you would like to roleplay, Please use the Instruct version.

⚔️ Hardware

  • 4x RTX 3090 GPUs
  • Epochs: 1
  • Base: Hamanasu-15B-R1-PT
  • Amount of Tokens: 500 Million

Axolotl Config ꒰(˶• ᴗ •˶)꒱

base_model: Hamanasu-15B-R2-PT
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

  #hub_model_id: NewEden/Phi4-pretrain
  #hub_strategy: "all_checkpoints"
  #push_dataset_to_hub:
  #hf_use_auth_token: true

plugins:
  - axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_swiglu: true
liger_fused_linear_cross_entropy: true

  #plugins:
  #  - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin

  #cut_cross_entropy: true

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: NewEden/Orion-LIT
    type: completion
    field: text
shuffle_merged_datasets: true
dataset_prepared_path: prepared_data
val_set_size: 0.0
output_dir: ./phi4-ptv2-out-r1

sequence_len: 16384
sample_packing: true
pad_to_sequence_len: true

adapter: lora
lora_model_dir:
lora_r: 128
lora_alpha: 16 
lora_dropout: 0.05
lora_target_modules:
  - gate_proj
  - down_proj
  - up_proj
  - q_proj
  - v_proj
  - k_proj
  - o_proj

lora_modules_to_save:
 - embed_tokens
 - lm_head


wandb_project: mag-phi
wandb_entity:
wandb_watch:
wandb_name: comp-v2-attempt-01
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 1
optimizer: paged_ademamix_8bit
lr_scheduler: cosine
learning_rate: 0.00002

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: unsloth
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 15
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 4
debug:
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16_cpuoffload_params.json
weight_decay: 0.01
fsdp:
fsdp_config:

⚡ Credits


Made by
Delta-Vector
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