qwen2-math-1_5b-step-dpo
This model is a fine-tuned version of Qwen/Qwen2-Math-1.5B-Instruct on the xinlai/Math-Step-DPO-10K 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: 5e-07
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8.0
Training results
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1.post300
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for rasdani/qwen2-math-1_5b-step-dpo
Base model
Qwen/Qwen2-Math-1.5B-Instruct