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M3-quantized-qlora-4bit – AI Model by bziemba | AlphaNeural AI
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M3-quantized-qlora-4bit
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peft
safetensors
llama-factory
lora
generated_from_trainer
Qwen/Qwen3-0.6B-Base
adapter
other
us
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qwen3-qlora-bnb
This model is a fine-tuned version of
Qwen/Qwen3-0.6B-Base
on the m3 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: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
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: 0.1
num_epochs: 3.0
Training results
Framework versions
PEFT 0.15.2
Transformers 4.52.3
Pytorch 2.6.0+cu126
Datasets 3.2.0
Tokenizers 0.21.0
