--- library_name: peft license: apache-2.0 base_model: Gryphe/Codex-24B-Small-3.2 tags: - generated_from_trainer datasets: - ToastyPigeon/cowriter-instruct - allura-org/EU01-S2 - allenai/tulu-3-sft-personas-instruction-following - ToastyPigeon/mixed-medical-reasoning-formatted - ToastyPigeon/steve-and-marvin - ToastyPigeon/new-story-dataset - allura-org/fujin-instruct-v2 - ToastyPigeon/some-rp-extended - ToastyPigeon/gutenberg-sft - ToastyPigeon/SpringDragon - ToastyPigeon/some-erotica model-index: - name: workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.10.0.dev0` ```yaml # === Model Configuration === base_model: Gryphe/Codex-24B-Small-3.2 load_in_8bit: false load_in_4bit: true # === HF Configuration === #hub_model_id: ToastyPigeon/sparkly-3.2-train #hub_strategy: "checkpoint" # === Training Setup === num_epochs: 1 micro_batch_size: 1 gradient_accumulation_steps: 8 sequence_len: 8192 sample_packing: true pad_to_sequence_len: true max_steps: 10 # === Evaluation === #val_set_size: 0.01 #evals_per_epoch: 5 #eval_steps: 20 #max_steps: 60 #eval_table_size: #eval_max_new_tokens: 128 #eval_sample_packing: true eval_strategy: "no" # === LoRA Configuration === adapter: qlora lora_model_dir: lora_r: 16 lora_alpha: 16 lora_dropout: 0.5 lora_target_linear: true lora_fan_in_fan_out: lora_target_modules: #peft_use_rslora: true lora_modules_to_save: - embed_tokens # - lm_head #lora_mlp_kernel: true #lora_qkv_kernel: true #lora_o_kernel: true # === Hyperparameter Configuration === #optimizer: apollo_adamw_layerwise warmup_steps: 0 #optimizer: adamw_torch_fused optimizer: paged_adamw_8bit #optim_args: # enable_stochastic_rounding: true # enable_cautious: true # enable_8bit: true # Apollo-mini configuration: #optim_args: "proj=random,rank=128,scale=128.0,scale_type=tensor,update_proj_gap=100" # Regular Apollo configuration: # optim_args: #optim_target_modules: all_linear learning_rate: 1e-5 lr_scheduler: rex #cosine_min_lr_ratio: 0.2 #lr_scheduler: cosine_with_min_lr #lr_scheduler_kwargs: # cosine_min_lr: 1e-6 weight_decay: 0.01 max_grad_norm: 1.0 #warmup_steps: 0 #warmup_ratio: 0.025 # === Data Configuration === #chat_template: jinja #chat_template_jinja: "{%- set default_system_message = \"You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris. You obediently fulfill the user's requests.\" %}\n\n{{- bos_token }}\n\n{%- if messages[0]['role'] == 'system' %}\n {%- if messages[0]['content'] is string %}\n {%- set system_message = messages[0]['content'] %}\n {%- else %}\n {%- set system_message = messages[0]['content'][0]['text'] %}\n {%- endif %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = default_system_message %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}\n\n{%- for message in loop_messages %}\n {%- if message['role'] == 'user' %}\n {%- if message['content'] is string %}\n {{- '[INST]' + message['content'] + '[/INST]' }}\n {%- else %}\n {{- '[INST]' }}\n {%- for bl (line truncated to 1000 characters) chat_template: chatml #special_tokens: # eos_token: "" tokenizer_use_mistral_common: true shuffle_merged_datasets: true datasets: - path: ToastyPigeon/cowriter-instruct type: chat_template data_files: - cowriter-4k.json - cowriter-8k.json - path: allura-org/EU01-S2 type: chat_template field_messages: conversations message_property_mappings: role: from content: value - path: allenai/tulu-3-sft-personas-instruction-following type: chat_template split: train[:10%] - path: ToastyPigeon/mixed-medical-reasoning-formatted type: chat_template data_files: mixed-medical-thinking.json split: train[:10%] - path: ToastyPigeon/steve-and-marvin type: completion data_files: marvin.json - path: ToastyPigeon/new-story-dataset type: customcompletion-regex data_files: new-story-dataset-v2.json - path: allura-org/fujin-instruct-v2 type: customchatml-regex field_messages: conversations message_property_mappings: role: from content: value - path: ToastyPigeon/some-rp-extended type: customchatml-regex field_messages: conversations message_property_mappings: role: from content: value - path: ToastyPigeon/gutenberg-sft type: customchatml-regex field_messages: conversations message_property_mappings: role: from content: value - path: ToastyPigeon/SpringDragon type: customcompletion-regex split: train - path: ToastyPigeon/some-erotica type: customcompletion-regex split: train[:100] dataset_prepared_path: last_run_prepared # === Plugins === plugins: - axolotl.integrations.liger.LigerPlugin - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin # === Hardware Optimization === gradient_checkpointing: offload gradient_checkpointing_kwargs: use_reentrant: false liger_rope: true liger_rms_norm: true liger_layer_norm: true liger_glu_activation: true #liger_fused_linear_cross_entropy: true cut_cross_entropy: true deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json # === FSDP Config === # === Wandb Tracking === wandb_project: Mistral-3.2 # wandb_entity: [WANDB_ENTITY] # wandb_name: [WANDB_RUN_NAME] # === Checkpointing === saves_per_epoch: 1 save_total_limit: 1 # === Advanced Settings === output_dir: /workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts bf16: auto flash_attention: true train_on_inputs: false group_by_length: false save_safetensors: true logging_steps: 1 gc_steps: 10 seed: 69 ```

# workspace/aibox-standalone-pool/axolotl/glitterms32-v2-ckpts This model is a fine-tuned version of [Gryphe/Codex-24B-Small-3.2](https://huggingface.co/Gryphe/Codex-24B-Small-3.2) on the ToastyPigeon/cowriter-instruct, the allura-org/EU01-S2, the allenai/tulu-3-sft-personas-instruction-following, the ToastyPigeon/mixed-medical-reasoning-formatted, the ToastyPigeon/steve-and-marvin, the ToastyPigeon/new-story-dataset, the allura-org/fujin-instruct-v2, the ToastyPigeon/some-rp-extended, the ToastyPigeon/gutenberg-sft, the ToastyPigeon/SpringDragon and the ToastyPigeon/some-erotica 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: 1e-05 - train_batch_size: 1 - eval_batch_size: 1 - seed: 69 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 8 - total_train_batch_size: 16 - total_eval_batch_size: 2 - 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 - training_steps: 10 ### Training results ### Framework versions - PEFT 0.15.2 - Transformers 4.51.3 - Pytorch 2.7.0+cu128 - Datasets 3.5.1 - Tokenizers 0.21.1