M-jack_experiments__all_stages-sft
This model was created as part of the jack_experiments__all_stages experiment using the SkillFactory experiment management system.
Model Details
- Training Method: LLaMAFactory SFT (Supervised Fine-Tuning)
- Stage Name: sft
- Experiment: jack_experiments__all_stages
Training Configuration
{"model_name_or_path": "Qwen/Qwen2.5-0.5B-Instruct", "trust_remote_code": true, "stage": "sft", "do_train": true, "finetuning_type": "full", "deepspeed": "/scratch/yl11330/skill-factory/thirdparty/LLaMA-Factory/examples/deepspeed/ds_z2_config.json", "dataset": "TAUR_dev__D_SFT_C_cd3arg_Qwen2_5_1_5B_Instruct_AnsRev_think", "template": "qwen", "cutoff_len": 16384, "max_samples": 10, "overwrite_cache": true, "preprocessing_num_workers": 1, "dataloader_num_workers": 0, "disable_tqdm": false, "output_dir": "/scratch/yl11330/skill-factory/workflow_out_mr3182/jack_experiments__all_stages/llamafactory/checkpoints", "logging_steps": 10, "save_steps": 100000, "plot_loss": true, "overwrite_output_dir": true, "per_device_train_batch_size": 1, "gradient_accumulation_steps": 1, "learning_rate": 1e-06, "num_train_epochs": 1, "lr_scheduler_type": "cosine", "warmup_ratio": 0.05, "weight_decay": 0.0001, "adam_beta1": 0.9, "adam_beta2": 0.95, "bf16": true, "ddp_timeout": 180000000, "gradient_checkpointing": true, "save_only_model": true, "enable_masked_ranges": false, "save_strategy": "steps", "save_total_limit": 5, "sf_tracker_dataset_id": "TAUR-dev/D-ExpTracker__jack_experiments__all_stages__v1", "sf_eval_before_training": false, "sf_wandb_project": "jacksft", "sf_eval_steps": null, "run_name": "jack_experiments__all_stages_sft"}
Experiment Tracking
🔗 View complete experiment details: Experiment Tracker Dataset
Usage
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("TAUR-dev/M-jack_experiments__all_stages-sft")
model = AutoModelForCausalLM.from_pretrained("TAUR-dev/M-jack_experiments__all_stages-sft")
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