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Qwen2.5-3B-Instruct-OT3-8K-QwQ-R1-LRDRMi – AI Model by hazyresearch | AlphaNeural AI
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Qwen2.5-3B-Instruct-OT3-8K-QwQ-R1-LRDRMi
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transformers
safetensors
qwen2
text-generation
llama-factory
full
generated_from_trainer
conversational
Qwen/Qwen2.5-3B-Instruct
finetune
other
text-generation-inference
endpoints_compatible
us
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Qwen2.5-3B-Instruct-OT3-8K-QwQ-R1-LRDRMi
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: 2
total_train_batch_size: 8
total_eval_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5.0
Training results
Framework versions
Transformers 4.52.4
Pytorch 2.7.1+cu126
Datasets 3.6.0
Tokenizers 0.21.1