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qwne3_4B_shortSFT – AI Model by Love2DL | AlphaNeural AI
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qwne3_4B_shortSFT
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transformers
safetensors
qwen3
text-generation
llama-factory
full
generated_from_trainer
conversational
Qwen/Qwen3-4B
finetune
other
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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qwne3_4B_shortSFT
This model is a fine-tuned version of
Qwen/Qwen3-4B
on the sft_data 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-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 12
total_train_batch_size: 96
total_eval_batch_size: 32
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: 3.0
Training results
Framework versions
Transformers 4.52.4
Pytorch 2.7.1+cu126
Datasets 3.6.0
Tokenizers 0.21.1
