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Aura-4B

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Introduction

Aura-4B is a state of the art dedicated roleplaying model designed to fulfill your every desire.

This finetune has seen several hundreds of millions of tokens of completion, instruction and roleplaying data. A Kahneman-Tversky Optimization was applied to give this model a unique output style.

Developed by Aura Industries, with contributions from Anthracite Org

Model Details

License

This model is licensed under the Apache 2.0 License.

Quantizations

Static GGUF

Imatrix GGUF

EXL2

Open LLM Leaderboard Evaluation Results

Coming soon...

Metric Value
Avg. N/A
IFEval (0-Shot) N/A
BBH (3-Shot) N/A
MATH Lvl 5 (4-Shot) N/A
GPQA (0-shot) N/A
MuSR (0-shot) N/A
MMLU-PRO (5-shot) N/A

Training Configuration

Click here for Axolotl configs

Completion SFT

base_model: IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: false
strict: false

hub_model_id: jeiku/completion4B
hub_strategy: "all_checkpoints"
push_dataset_to_hub:
hf_use_auth_token: true

datasets:
  - path: Mielikki/Erebus-87k
    type: completion
    field: body

shuffle_merged_datasets: true
val_set_size: 0.0025
output_dir: ./outputs/out

adapter:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:

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

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

wandb_project: EXP4B
wandb_entity:
wandb_watch:
wandb_name: EXP4B
wandb_log_model:

gradient_accumulation_steps: 12
micro_batch_size: 3
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.00001
weight_decay: 0.05

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

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

warmup_ratio: 0.1
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1

debug:
deepspeed: deepspeed_configs/zero3_bf16.json
fsdp:
fsdp_config:

special_tokens:
  pad_token: <|finetune_right_pad_id|>

Instruct SFT

base_model: jeiku/completion4B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: false
strict: false

hub_model_id: jeiku/instructered4B
hub_strategy: "all_checkpoints"
push_dataset_to_hub:
hf_use_auth_token: true

datasets:
  - path: FourOhFour/Instruct_Phase
    type: sharegpt
    conversation: chatml

chat_template: chatml

shuffle_merged_datasets: true
val_set_size: 0.0025
output_dir: ./outputs/out

adapter:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:

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

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

wandb_project: EXP4B
wandb_entity:
wandb_watch:
wandb_name: EXP4B
wandb_log_model:

gradient_accumulation_steps: 12
micro_batch_size: 3
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.00001
weight_decay: 0.05

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

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

warmup_ratio: 0.1
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 2

debug:
deepspeed: deepspeed_configs/zero3_bf16.json
fsdp:
fsdp_config:

special_tokens:
  pad_token: <|finetune_right_pad_id|>

Roleplaying SFT

base_model: jeiku/instructered4B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: false
strict: false

hub_model_id: jeiku/TheBest4B
hub_strategy: "all_checkpoints"
push_dataset_to_hub:
hf_use_auth_token: true

datasets:
  - path: FourOhFour/RP_Phase
    type: sharegpt
    conversation: chatml

chat_template: chatml

shuffle_merged_datasets: true
val_set_size: 0.0025
output_dir: ./outputs/out

adapter:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:

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

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

wandb_project: EXP4B
wandb_entity:
wandb_watch:
wandb_name: EXP4B
wandb_log_model:

gradient_accumulation_steps: 12
micro_batch_size: 3
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.00001
weight_decay: 0.05

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

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

warmup_ratio: 0.1
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 2

debug:
deepspeed: deepspeed_configs/zero3_bf16.json
fsdp:
fsdp_config:

special_tokens:
  pad_token: <|finetune_right_pad_id|>

KTO

base_model: FourOhFour/Crispy_Crab_4B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: false
strict: false

hub_model_id: jeiku/aura4bkto
hub_strategy: "all_checkpoints"
push_dataset_to_hub:
hf_use_auth_token: true

chat_template: chatml

rl: kto
rl_beta: 0.2
kto_desirable_weight: 0.2

datasets:
  - path: anthracite-core/full-opus-chosen-hermes-rejected-kto-v1
    type: chatml.argilla

shuffle_merged_datasets: true
val_set_size: 0.0
output_dir: ./outputs/out

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

wandb_project: Aura-4B
wandb_entity:
wandb_watch:
wandb_name: Aura-4B
wandb_log_model:

gradient_accumulation_steps: 16
micro_batch_size: 2
num_epochs: 2
max_steps: 500

optimizer: adamw_8bit
lr_scheduler: cosine
learning_rate: 0.00001
weight_decay: 0.05

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

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

warmup_steps: 10
evals_per_epoch: 2
eval_table_size:
eval_max_new_tokens: 
saves_per_epoch: 1

debug:
deepspeed: 
fsdp:
fsdp_config:
fsdp:
fsdp_config:

special_tokens:
  pad_token: <|finetune_right_pad_id|>

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