Noodles-12B

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<details><summary>See axolotl config</summary>

axolotl version: 0.8.0

## model
base_model: hardlyworking/Broth-12B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
## upload
hub_model_id: hardlyworking/Noodles-12B
hub_strategy: "all_checkpoints"
push_dataset_to_hub:
hf_use_auth_token: true
## qlora COPE
load_in_8bit: false
load_in_4bit: false
strict: false

## data 
datasets:
  - path: PocketDoc/Dans-MemoryCore-CoreCurriculum-Small
    type: dan-chat-advanced
  - path: NewEden/Kalo-Opus-Instruct-22k-Refusal-Murdered
    type: dan-chat-advanced
  - path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
    type: dan-chat-advanced
  - path: Nitral-AI/Reasoning-1shot_ShareGPT
    type: dan-chat-advanced
  - path: Nitral-AI/GU_Instruct-ShareGPT
    type: dan-chat-advanced
  - path: Nitral-AI/Medical_Instruct-ShareGPT
    type: dan-chat-advanced
  - path: AquaV/Resistance-Sharegpt
    type: dan-chat-advanced
  - path: AquaV/US-Army-Survival-Sharegpt
    type: dan-chat-advanced
  - path: Gryphe/Sonnet3.5-SlimOrcaDedupCleaned
    type: dan-chat-advanced

shuffle_merged_datasets: true
dataset_prepared_path: dataset_prepared
val_set_size: 0.001
output_dir: outputs/out

## LIGER & CCE
plugins:
  - axolotl.integrations.liger.LigerPlugin
  - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
liger_fused_linear_cross_entropy: false
cut_cross_entropy: false

## CTX settings
sequence_len: 8192
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true

## Lora 
adapter: lora
lora_model_dir:
lora_r: 128
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
peft_use_rslora: true
lora_modules_to_save:
  - embed_tokens
  - lm_head

## WandB
wandb_project: JoeyBoy
wandb_entity:
wandb_watch:
wandb_name: 
wandb_log_model:

## evals
evals_per_epoch: 8
eval_table_size:
eval_max_new_tokens: 128

## hoe params
gradient_accumulation_steps: 2
micro_batch_size: 4
num_epochs: 2
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 2e-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
s2_attention:

warmup_steps: 40
saves_per_epoch: 2
debug:
## for ademiamix 
deepspeed: ./deepspeed_configs/zero3_bf16.json
## for adamw
#deepspeed: ./deepspeed_configs/zero3_bf16.json
weight_decay: 0.01
fsdp:
fsdp_config:
special_tokens:
   pad_token: <pad>

</details><br>

Noodles-12B

This model is a fine-tuned version of hardlyworking/Broth-12B on the PocketDoc/Dans-MemoryCore-CoreCurriculum-Small, the NewEden/Kalo-Opus-Instruct-22k-Refusal-Murdered, the Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned, the Nitral-AI/Reasoning-1shot_ShareGPT, the Nitral-AI/GU_Instruct-ShareGPT, the Nitral-AI/Medical_Instruct-ShareGPT, the AquaV/Resistance-Sharegpt, the AquaV/US-Army-Survival-Sharegpt and the Gryphe/Sonnet3.5-SlimOrcaDedupCleaned datasets. It achieves the following results on the evaluation set:

• Loss: 0.7255

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• total_eval_batch_size: 16
• optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 40
• num_epochs: 2.0

Training results

Framework versions

• PEFT 0.15.1
• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1