--- library_name: transformers base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct tags: - llama-factory - full - generated_from_trainer model-index: - name: train-armv8-O2_epoch1and2 results: [] --- # train-armv8-O2_epoch1and2 This model is a fine-tuned version of [saves/train-armv8-O2_epoch1and2/checkpoint-3200](https://huggingface.co/saves/train-armv8-O2_epoch1and2/checkpoint-3200) on the train-armv8-O2-verbose_part_00, the train-armv8-O2-verbose_part_01, the train-armv8-O2-verbose_part_02, the train-armv8-O2-verbose_part_03, the train-armv8-O2-verbose_part_04, the train-armv8-O2-verbose_part_05, the train-armv8-O2-verbose_part_06, the train-armv8-O2-verbose_part_07, the train-armv8-O2-verbose_part_08, the train-armv8-O2-verbose_part_09, the train-armv8-O2-verbose_part_10, the train-armv8-O2-verbose_part_11, the train-armv8-O2-verbose_part_12, the train-armv8-O2-verbose_part_13, the train-armv8-O2-verbose_part_14, the train-armv8-O2-verbose_part_15, the train-armv8-O2-verbose_part_16, the train-armv8-O2-verbose_part_17, the train-armv8-O2-verbose_part_18, the train-armv8-O2-verbose_part_19, the train-armv8-O2-verbose_part_20, the train-armv8-O2-verbose_part_21, the train-armv8-O2-verbose_part_22, the train-armv8-O2-verbose_part_23, the train-armv8-O2-verbose_part_24, the train-armv8-O2-verbose_part_25, the train-armv8-O2-verbose_part_26, the train-armv8-O2-verbose_part_27, the train-armv8-O2-verbose_part_28, the train-armv8-O2-verbose_part_29, the train-armv8-O2-verbose_part_30, the train-armv8-O2-verbose_part_31, the train-armv8-O2-verbose_part_32, the train-armv8-O2-verbose_part_33, the train-armv8-O2-verbose_part_34, the train-armv8-O2-verbose_part_35, the train-armv8-O2-verbose_part_36, the train-armv8-O2-verbose_part_37, the train-armv8-O2-verbose_part_38, the train-armv8-O2-verbose_part_39, the train-armv8-O2-verbose_part_40 and the train-armv8-O2-verbose_part_41 datasets. ## 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: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 8 - total_train_batch_size: 512 - total_eval_batch_size: 64 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 2.0 ### Training results ### Framework versions - Transformers 4.55.0 - Pytorch 2.8.0+rocm6.3 - Datasets 3.6.0 - Tokenizers 0.21.1