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---
license: apache-2.0
datasets:
- Mielikki/Erebus-87k
- FourOhFour/Instruct_Phase
- FourOhFour/RP_Phase
- anthracite-core/full-opus-chosen-hermes-rejected-kto-v1
language:
- en
base_model:
- IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml
---
---
### These are EXL2 quants for Aura-4B, Measurement file in the main branch, Check revisions for different BPW
---
## Aura-4B
## 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
- **Model Name**: Aura-4B
- **Base Model**: [IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml](https://huggingface.co/IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml)
- **Model Type**: Chat Completions
- **Prompt Format**: ChatML
- **License**: Apache-2.0
- **Language**: English
- **Max Context**: 8,192+ tokens
## License
This model is licensed under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0).
## Quantizations
[Static GGUF](https://huggingface.co/mradermacher/Aura-4B-GGUF)
[Imatrix GGUF](https://huggingface.co/mradermacher/Aura-4B-i1-GGUF)
EXL2 coming soon...
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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
<details><summary>Click here for Axolotl configs</summary>
Completion SFT
```yaml
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
```yaml
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
```yaml
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
```yaml
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|>
```
</details><br> |