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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: kakaocorp/kanana-1.5-2.1b-instruct-2505 |
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tags: |
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- axolotl |
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- generated_from_trainer |
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datasets: |
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- train.jsonl |
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model-index: |
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- name: fc-reasoning-2.1b |
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results: [] |
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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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[<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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axolotl version: `0.12.2` |
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```yaml |
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base_model: kakaocorp/kanana-1.5-2.1b-instruct-2505 |
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load_in_8bit: false |
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load_in_4bit: false |
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datasets: |
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- path: train.jsonl |
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type: chat_template |
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dataset_prepared_path: preprocess |
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val_set_size: 0.01 |
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output_dir: ./outputs |
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dataloader_num_workers: 56 |
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adapter: |
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lora_model_dir: |
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sequence_len: 16384 |
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sample_packing: false |
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eval_sample_packing: false |
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pad_to_sequence_len: false |
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plugins: |
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- axolotl.integrations.liger.LigerPlugin |
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liger_rope: true |
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liger_rms_norm: true |
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liger_swiglu: true |
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liger_fused_linear_cross_entropy: true |
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wandb_project: fastcampus |
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wandb_entity: guijinson |
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wandb_watch: |
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wandb_name: fc-proj2-reasoning-2.1b |
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wandb_log_model: |
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hub_model_id: amphora/fc-reasoning-2.1b |
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gradient_accumulation_steps: 64 |
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micro_batch_size: 2 |
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num_epochs: 3 |
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optimizer: adamw_torch_fused |
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lr_scheduler: cosine |
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learning_rate: 2e-5 |
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bf16: auto |
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tf32: false |
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gradient_checkpointing: |
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resume_from_checkpoint: |
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logging_steps: 1 |
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flash_attention: true |
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warmup_ratio: 0.05 |
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weight_decay: 0.01 |
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evals_per_epoch: 0 |
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saves_per_epoch: 1 |
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``` |
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</details><br> |
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# fc-reasoning-2.1b |
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This model is a fine-tuned version of [kakaocorp/kanana-1.5-2.1b-instruct-2505](https://huggingface.co/kakaocorp/kanana-1.5-2.1b-instruct-2505) on the train.jsonl dataset. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 128 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 53 |
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- training_steps: 1072 |
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### Training results |
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### Framework versions |
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- Transformers 4.55.2 |
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- Pytorch 2.6.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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