v49 Public091 LoRA R32 Lr2e4 Ep1

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0002
• train_batch_size: 1
• eval_batch_size: 8
• seed: 202607199
• gradient_accumulation_steps: 4
• total_train_batch_size: 4
• optimizer: Use OptimizerNames.ADAMW_TORCH 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: 0.03
• num_epochs: 1.0

Training results

Framework versions

• PEFT 0.18.1
• Transformers 5.6.0
• Pytorch 2.7.1+cu126
• Datasets 4.0.0
• Tokenizers 0.22.2

--- library_name: peft license: other base_model: OpenOneRec/OneReason-0.8B-pretrain-competition tags: - base_model:adapter:OpenOneRec/OneReason-0.8B-pretrain-competition - llama-factory - lora - transformers pipeline_tag: text-generation model-index: - name: v49_public091_lora_r32_lr2e4_ep1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # v49_public091_lora_r32_lr2e4_ep1 This model is a fine-tuned version of [OpenOneRec/OneReason-0.8B-pretrain-competition](https://huggingface.co/OpenOneRec/OneReason-0.8B-pretrain-competition) on the exp_v49_public_091_exact dataset. ## 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: 0.0002 - train_batch_size: 1 - eval_batch_size: 8 - seed: 202607199 - gradient_accumulation_steps: 4 - total_train_batch_size: 4 - optimizer: Use OptimizerNames.ADAMW_TORCH 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: 0.03 - num_epochs: 1.0 ### Training results ### Framework versions - PEFT 0.18.1 - Transformers 5.6.0 - Pytorch 2.7.1+cu126 - Datasets 4.0.0 - Tokenizers 0.22.2