OpenR1-Math-Raw-all-correct-5k

This model is a fine-tuned version of open-thoughts/OpenThinker2-7B on the neginr/OpenR1-Math-Raw-all-correct-5k 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: 2e-07
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 32
• gradient_accumulation_steps: 3
• total_train_batch_size: 96
• total_eval_batch_size: 256
• 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_ratio: 0.1
• num_epochs: 7.0

Training results

Framework versions

• Transformers 4.46.1
• Pytorch 2.5.1
• Datasets 3.0.2
• Tokenizers 0.20.3