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capsd-qwen35-numina-Qwen3.5-4B-Base-math_cap_b2000_s0 – AI Model by AmberYifan | AlphaNeural AI
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AmberYifan
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capsd-qwen35-numina-Qwen3.5-4B-Base-math_cap_b2000_s0
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transformers
safetensors
qwen3_5
image-text-to-text
llama-factory
full
generated_from_trainer
conversational
Qwen/Qwen3.5-4B-Base
finetune
other
endpoints_compatible
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Qwen3.5-4B-Base_math_cap_b2000_s0
This model is a fine-tuned version of
Qwen/Qwen3.5-4B-Base
on the capsd_Qwen3.5-4B-Base-n80000-numina__mix_math_cap_b2000_s0 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: 2
eval_batch_size: 8
seed: 0
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 8
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_steps: 0.03
num_epochs: 1
Training results
Framework versions
Transformers 5.8.0
Pytorch 2.13.0+cu130
Datasets 4.0.0
Tokenizers 0.22.2
