--- library_name: peft license: apache-2.0 base_model: allura-org/TQ2.5-14B-Sugarquill-v1 tags: - axolotl - generated_from_trainer datasets: - Nitral-AI/Creative_Writing-ShareGPT - Nitral-AI/ARES-ShareGPT - NewEden/Claude-Instruct-5K - NewEden/OpenCAI-ShareGPT - NewEden/PIPPA-Mega-Filtered - NewEden/Roleplay-Logs-Sharegpt-Ngram-cleaned - Nitral-AI/Creative_Writing-ShareGPT model-index: - name: control-14b-lora results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.6.0` ```yaml base_model: allura-org/TQ2.5-14B-Sugarquill-v1 strict: false plugins: - axolotl.integrations.liger.LigerPlugin liger_rope: true liger_rms_norm: true liger_swiglu: true liger_fused_linear_cross_entropy: false liger_cross_entropy: false # Output and HuggingFace hub_model_id: NewEden/control-14b-lora hf_use_auth_token: true hub_strategy: "all_checkpoints" output_dir: ./outputs/ wandb_project: huggingface wandb_entity: wandb_name: Control-14B chat_template: chatml group_by_length: false datasets: - path: Nitral-AI/Creative_Writing-ShareGPT type: chat_template roles_to_train: ["gpt"] field_messages: conversations message_field_role: from message_field_content: value train_on_eos: turn - path: Nitral-AI/ARES-ShareGPT type: chat_template chat_template: chatml 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: chatml roles_to_train: ["gpt"] field_messages: conversations message_field_role: from message_field_content: value train_on_eos: turn - path: NewEden/OpenCAI-ShareGPT type: chat_template roles_to_train: ["gpt"] field_messages: conversations message_field_role: from message_field_content: value train_on_eos: turn - path: NewEden/PIPPA-Mega-Filtered type: chat_template chat_template: chatml roles_to_train: ["gpt"] field_messages: conversations message_field_role: from message_field_content: value train_on_eos: turn - path: NewEden/Roleplay-Logs-Sharegpt-Ngram-cleaned type: chat_template chat_template: chatml 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: chatml roles_to_train: ["gpt"] field_messages: conversations message_field_role: from message_field_content: value train_on_eos: turn #val_set_size: 0.01 #evals_per_epoch: 1 # eval_table_size: # eval_max_new_tokens: 128 num_epochs: 2 sequence_len: 8192 save_safetensors: true saves_per_epoch: 2 logging_steps: 1 special_tokens: # Quantization bf16: auto fp16: tf32: false ## For LoRA load_in_8bit: false load_in_4bit: True # LoRA peft_use_rslora: true adapter: qlora lora_model_dir: lora_r: 128 lora_alpha: 16 lora_dropout: 0.05 lora_target_linear: true lora_fan_in_fan_out: lora_target_modules: ## if oom # lora_r: 64 # lora_alpha: 32 # lora_dropout: 0.1 weight_decay: 0.02 max_grad_norm: 1.0 warmup_ratio: 0.05 learning_rate: 0.00002 lr_scheduler: cosine #lr_scheduler_kwargs: optimizer: paged_adamw_8bit # usually adamw_torch or paged_adamw_8bit ## Batch Size gradient_accumulation_steps: 8 micro_batch_size: 1 eval_batch_size: 1 # Optimizations pad_to_sequence_len: true sample_packing: true eval_sample_packing: false flash_attention: true xformers_attention: gradient_checkpointing: "unsloth" gradient_checkpointing_kwargs: use_reentrant: true local_rank: early_stopping_patience: debug: special_tokens: pad_token: <|endoftext|> eos_token: <|im_end|> ```

# control-14b-lora This model is a fine-tuned version of [allura-org/TQ2.5-14B-Sugarquill-v1](https://huggingface.co/allura-org/TQ2.5-14B-Sugarquill-v1) on the Nitral-AI/Creative_Writing-ShareGPT, the Nitral-AI/ARES-ShareGPT, the NewEden/Claude-Instruct-5K, the NewEden/OpenCAI-ShareGPT, the NewEden/PIPPA-Mega-Filtered, the NewEden/Roleplay-Logs-Sharegpt-Ngram-cleaned and the Nitral-AI/Creative_Writing-ShareGPT datasets. ## 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: 1 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 8 - 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: 43 - num_epochs: 2 ### Training results ### Framework versions - PEFT 0.14.0 - Transformers 4.47.1 - Pytorch 2.3.1+cu121 - Datasets 3.1.0 - Tokenizers 0.21.0