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DinoQwen3-4B-DASD – AI Model by Djapamal | AlphaNeural AI | AlphaNeural AI
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Djapamal
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DinoQwen3-4B-DASD
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peft
safetensors
qwen3
text-generation
adapter
llama-factory
lora
transformers
conversational
unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit
other
text-generation-inference
endpoints_compatible
4-bit
bitsandbytes
us
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stage2
This model is a fine-tuned version of
unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit
on the train_stage_2 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: 0.0001
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.15
num_epochs: 3.0
Training results
Framework versions
PEFT 0.18.1
Transformers 5.2.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
