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qwen2_coder_reflct_adamw_iter1

This model is a fine-tuned version of Qwen/Qwen2.5-Coder-1.5B-Instruct on the self-generate/qwcoder2_reflct_original_cn_mining_oj_iter0-binarized-reflection-scored 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: 1e-06
  • train_batch_size: 8
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 64
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant
  • lr_scheduler_warmup_ratio: 0.1
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 1.0

Training results

Framework versions

  • Transformers 4.45.0
  • Pytorch 2.4.0+cu121
  • Datasets 2.14.6
  • Tokenizers 0.20.1
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Dataset used to train yiran-wang3/qwen2_coder_reflct_adamw_iter1