--- library_name: transformers base_model: minpeter/tiny-ko-base tags: - axolotl - generated_from_trainer datasets: - lemon-mint/Korean-FineTome-100k - lemon-mint/smol-koreantalk - heegyu/open-korean-instructions-v20231020 - FreedomIntelligence/evol-instruct-korean - FreedomIntelligence/alpaca-gpt4-korean - FreedomIntelligence/sharegpt-korean - coastral/korean-writing-style-instruct - devngho/korean-instruction-mix - youjunhyeok/Magpie-Pro-300K-Filtered-ko - youjunhyeok/smoltalk-ko-translate model-index: - name: tiny-ko-sft results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.10.0.dev0` ```yaml base_model: minpeter/tiny-ko-base hub_model_id: minpeter/tiny-ko-sft output_dir: ./outputs/tiny-ko-sft wandb_project: "axolotl" wandb_entity: "kasfiekfs-e" chat_template: chatml datasets: - path: lemon-mint/Korean-FineTome-100k type: chat_template split: train[:10%] field_messages: messages message_property_mappings: role: role content: content - path: lemon-mint/smol-koreantalk type: chat_template split: train[:10%] field_messages: messages message_property_mappings: role: role content: content - path: heegyu/open-korean-instructions-v20231020 type: chat_template split: train[:10%] field_messages: conversations message_property_mappings: role: from content: value roles: user: ["human", "user"] assistant: ["gpt", "assistant", "bot"] system: ["system", "input"] # NOTE: https://github.com/FreedomIntelligence/MultilingualSIFT - path: FreedomIntelligence/evol-instruct-korean type: chat_template split: train[:10%] field_messages: conversations message_property_mappings: role: from content: value - path: FreedomIntelligence/alpaca-gpt4-korean type: chat_template split: train[:10%] field_messages: conversations message_property_mappings: role: from content: value - path: FreedomIntelligence/sharegpt-korean type: chat_template split: train[:10%] field_messages: conversations message_property_mappings: role: from content: value - path: coastral/korean-writing-style-instruct type: chat_template split: train[:10%] field_messages: conversations message_property_mappings: role: from content: value - path: devngho/korean-instruction-mix type: chat_template split: train[:10%] field_messages: messages message_property_mappings: role: from content: value - path: youjunhyeok/Magpie-Pro-300K-Filtered-ko type: chat_template split: train[:10%] field_messages: conversations message_property_mappings: role: from content: value - path: youjunhyeok/smoltalk-ko-translate type: chat_template name: merge_filtered field_messages: conversations message_property_mappings: role: role content: content dataset_prepared_path: last_run_prepared val_set_size: 0.05 save_steps: 200 warmup_steps: 20 eval_steps: 200 sequence_len: 4096 # <<<< experimental settings <<<< sample_packing: true train_on_inputs: false # >>>> experimental settings >>> pad_to_sequence_len: true gradient_accumulation_steps: 4 micro_batch_size: 32 optimizer: paged_adamw_8bit lr_scheduler: cosine learning_rate: 1e-3 bf16: auto tf32: false gradient_checkpointing: true gradient_checkpointing_kwargs: use_reentrant: false resume_from_checkpoint: logging_steps: 1 flash_attention: true num_epochs: 1 weight_decay: 0.0 ```

# tiny-ko-sft This model is a fine-tuned version of [minpeter/tiny-ko-base](https://huggingface.co/minpeter/tiny-ko-base) on the lemon-mint/Korean-FineTome-100k, the lemon-mint/smol-koreantalk, the heegyu/open-korean-instructions-v20231020, the FreedomIntelligence/evol-instruct-korean, the FreedomIntelligence/alpaca-gpt4-korean, the FreedomIntelligence/sharegpt-korean, the coastral/korean-writing-style-instruct, the devngho/korean-instruction-mix, the youjunhyeok/Magpie-Pro-300K-Filtered-ko and the youjunhyeok/smoltalk-ko-translate datasets. It achieves the following results on the evaluation set: - Loss: 1.5297 ## 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: 0.001 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 4 - total_train_batch_size: 256 - total_eval_batch_size: 64 - 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: 20 - training_steps: 817 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 2.3518 | 0.0012 | 1 | 2.3640 | | 1.6322 | 0.2446 | 200 | 1.6913 | | 1.5903 | 0.4891 | 400 | 1.6003 | | 1.5146 | 0.7337 | 600 | 1.5392 | | 1.5277 | 0.9783 | 800 | 1.5297 | ### Framework versions - Transformers 4.52.3 - Pytorch 2.6.0+cu124 - Datasets 3.6.0 - Tokenizers 0.21.1