Aura-8B
Introduction
Aura-8B 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 instruction and roleplaying data. A Kahneman-Tversky Optimization was applied as a Low Rank Adapter to give this model a unique output style.
Developed by Aura Industries, with contributions from Anthracite Org
Model Details
- Model Name: Aura-8B
- Base Model: arcee-ai/Llama-3.1-SuperNova-Lite
- Model Type: Chat Completions
- Prompt Format: Llama 3
- License: Apache-2.0
- Language: English
- Max Context: 8,192+ tokens
License
This model is licensed under the Apache 2.0 License.
Quantizations
Open LLM Leaderboard Evaluation Results
| Metric | Value |
|---|---|
| Avg. | 27.34 |
| IFEval (0-Shot) | 72.05 |
| BBH (3-Shot) | 30.98 |
| MATH Lvl 5 (4-Shot) | 15.03 |
| GPQA (0-shot) | 4.81 |
| MuSR (0-shot) | 9.22 |
| MMLU-PRO (5-shot) | 31.93 |
Training Configuration
SFT
base_model: arcee-ai/Llama-3.1-SuperNova-Lite
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: FourOhFour/RP_Phase
type: chat_template
chat_template: llama3
roles_to_train: ["gpt"]
field_messages: conversations
message_field_role: from
message_field_content: value
train_on_eos: turn
- path: Nitral-AI/Cybersecurity-ShareGPT
type: chat_template
chat_template: llama3
roles_to_train: ["gpt"]
field_messages: conversations
message_field_role: from
message_field_content: value
train_on_eos: turn
- path: Nitral-AI/Medical_Instruct-ShareGPT
type: chat_template
chat_template: llama3
roles_to_train: ["gpt"]
field_messages: conversations
message_field_role: from
message_field_content: value
train_on_eos: turn
- path: Nitral-AI/Olympiad_Math-ShareGPT
type: chat_template
chat_template: llama3
roles_to_train: ["gpt"]
field_messages: conversations
message_field_role: from
message_field_content: value
train_on_eos: turn
- path: NewEden/Claude-Instruct-5k
type: chat_template
chat_template: llama3
roles_to_train: ["gpt"]
field_messages: conversations
message_field_role: from
message_field_content: value
train_on_eos: turn
- path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered
type: chat_template
chat_template: llama3
roles_to_train: ["gpt"]
field_messages: conversations
message_field_role: from
message_field_content: value
train_on_eos: turn
- path: Nitral-AI/Creative_Writing-ShareGPT
type: chat_template
chat_template: llama3
roles_to_train: ["gpt"]
field_messages: conversations
message_field_role: from
message_field_content: value
train_on_eos: turn
- path: jeiku/Writing
type: completion
field: text
shuffle_merged_datasets: true
dataset_prepared_path:
val_set_size: 0.01
output_dir: ./output/out
hub_model_id: jeiku/Aura-8B
hub_strategy: "all_checkpoints"
push_dataset_to_hub:
hf_use_auth_token: true
sequence_len: 8192
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len:
wandb_project: Aura-8B
wandb_entity:
wandb_watch:
wandb_name: Aura-8B
wandb_log_model:
gradient_accumulation_steps: 16
micro_batch_size: 2
num_epochs: 2
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 1e-5
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
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: 2
eval_table_size:
eval_max_new_tokens:
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.05
fsdp:
fsdp_config:
special_tokens:
pad_token: <|finetune_right_pad_id|>
eos_token: <|eot_id|>
KTO
base_model: jeiku/Aura-8B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
hub_model_id: jeiku/aurakto
hub_strategy: "all_checkpoints"
push_dataset_to_hub:
hf_use_auth_token: true
chat_template: llama3
rl: kto
rl_beta: 0.2
kto_desirable_weight: 0.2
datasets:
- path: anthracite-core/full-opus-chosen-hermes-rejected-kto-v1
type: llama3.argilla
shuffle_merged_datasets: true
val_set_size: 0.0
output_dir: ./outputs/out
adapter: lora
lora_model_dir:
lora_r: 32
lora_alpha: 64
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
sequence_len: 8192
sample_packing: false
eval_sample_packing: false
pad_to_sequence_len: false
wandb_project: Aura-8B
wandb_entity:
wandb_watch:
wandb_name: Aura-8B
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: 0.0001
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|>
eos_token: <|eot_id|>