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llavaqwen3-1.7b-finetune-nm-mask-moe-sparse-4e-2k-2of4-impinit-lr5e-4-denseres_20260726_211210 – AI Model by KKHYA | AlphaNeural AI
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KKHYA
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llavaqwen3-1.7b-finetune-nm-mask-moe-sparse-4e-2k-2of4-impinit-lr5e-4-denseres_20260726_211210
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transformers
pytorch
safetensors
nm_mask_moe_llava_qwen3
text-generation
generated_from_trainer
conversational
KKHYA/llavaqwen3-1.7b-finetune
finetune
apache-2.0
endpoints_compatible
us
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llavaqwen3-1.7b-finetune-nm-mask-moe-sparse-4e-2k-2of4-impinit-lr5e-4-denseres_20260726_211210
This model is a fine-tuned version of
KKHYA/llavaqwen3-1.7b-finetune
on an unknown 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: 0.0005
train_batch_size: 2
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 8
total_train_batch_size: 128
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: 0.03
num_epochs: 1.0
Training results
Framework versions
Transformers 4.51.0
Pytorch 2.5.1+cu121
Tokenizers 0.21.4
