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+ ---
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+ license: gemma
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+ base_model: google/gemma-2-9b
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: magnum-v3-9b-customgemma2
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+ results: []
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+ ---
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+ ### exl2 quant (measurement.json in main branch)
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+ ---
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+ ### check revisions for quants
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+ ---
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+
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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+ <details><summary>See axolotl config</summary>
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+
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+ axolotl version: `0.4.1`
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+ ```yaml
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+ base_model: google/gemma-2-9b
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+
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+ #trust_remote_code: true
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+
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+ load_in_8bit: false
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+ load_in_4bit: false
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+ strict: false
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+
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+ datasets:
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+ - path: anthracite-org/stheno-filtered-v1.1
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+ type: customgemma2
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+ - path: anthracite-org/kalo-opus-instruct-22k-no-refusal
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+ type: customgemma2
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+ - path: anthracite-org/nopm_claude_writing_fixed
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+ type: customgemma2
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+ - path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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+ type: customgemma2
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+ - path: Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
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+ type: customgemma2
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+ shuffle_merged_datasets: true
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+ default_system_message: "You are an assistant that responds to the user."
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+ dataset_prepared_path: magnum-v3-9b-data-customgemma2
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+ val_set_size: 0.0
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+ output_dir: ./magnum-v3-9b-customgemma2
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+
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+ sequence_len: 8192
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+ sample_packing: true
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+ eval_sample_packing: false
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+ pad_to_sequence_len:
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+
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+ adapter:
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+ lora_model_dir:
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+ lora_r:
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+ lora_alpha:
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+ lora_dropout:
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+ lora_target_linear:
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+ lora_fan_in_fan_out:
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+
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+ wandb_project: magnum-9b
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+ wandb_entity:
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+ wandb_watch:
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+ wandb_name: attempt-03-customgemma2
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+ wandb_log_model:
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+
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+ gradient_accumulation_steps: 8
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+ micro_batch_size: 1
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+ num_epochs: 2
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+ optimizer: paged_adamw_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 0.000006
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+
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+ train_on_inputs: false
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+ group_by_length: false
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+ bf16: auto
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+ fp16:
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+ tf32: false
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+
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+ gradient_checkpointing: unsloth
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+ early_stopping_patience:
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+ resume_from_checkpoint:
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+ local_rank:
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+ logging_steps: 1
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+ xformers_attention:
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+ flash_attention: false
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+ eager_attention: true
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+
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+ warmup_steps: 50
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+ evals_per_epoch:
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+ eval_table_size:
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+ eval_max_new_tokens:
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+ saves_per_epoch: 2
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+ debug:
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+ deepspeed: deepspeed_configs/zero3_bf16.json
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+ weight_decay: 0.05
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+ fsdp:
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+ fsdp_config:
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+ special_tokens:
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+ ```
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+
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+ </details><br>
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+
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+ # magnum-v3-9b-customgemma2
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+
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+ This model is a fine-tuned version of [google/gemma-2-9b](https://huggingface.co/google/gemma-2-9b) on the None dataset.
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 6e-06
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 8
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 64
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+ - total_eval_batch_size: 8
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 50
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+ - num_epochs: 2
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.0
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1