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Qwen2.5-32B-Instruct_simple_r1_v6_ep4_bs2 – AI Model by yiboowang | AlphaNeural AI
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Qwen2.5-32B-Instruct_simple_r1_v6_ep4_bs2
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transformers
safetensors
qwen2
text-generation
llama-factory
full
generated_from_trainer
conversational
Qwen/Qwen2.5-32B-Instruct
finetune
other
autotrain_compatible
text-generation-inference
endpoints_compatible
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Qwen2.5-32B—Instruct_simple_r1_v6_ep4_bs2
This model is a fine-tuned version of
/nfs/ofs-llm-ssd/models/opensource/Qwen2.5-32B-Instruct/
on the r1math_5k_simplify_v6 dataset. It achieves the following results on the evaluation set:
Loss: 0.5409
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: 1
seed: 42
distributed_type: multi-GPU
num_devices: 16
gradient_accumulation_steps: 2
total_train_batch_size: 32
total_eval_batch_size: 16
optimizer: Use 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: 4.0
Training results
Framework versions
Transformers 4.46.1
Pytorch 2.4.0+cu121
Datasets 3.1.0
Tokenizers 0.20.3
