rubricreward/R3-DeepSeek-R1-Distill-Qwen-14B-14k

qwen25_dpsk_14b_full_14k

This model is a fine-tuned version of deepseek-ai/DeepSeek-R1-Distill-Qwen-14B on the r3_dataset_14k 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-05
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 16
• total_train_batch_size: 64
• total_eval_batch_size: 32
• 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: 5

Training results

Framework versions

• Transformers 4.52.4
• Pytorch 2.6.0
• Datasets 3.6.0
• Tokenizers 0.21.1