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csqa-gwen3-distilled – AI Model by Maxime272003 | AlphaNeural AI
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csqa-gwen3-distilled
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csqa_stage2
This model is a fine-tuned version of
unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit
on the csqa_stage2 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: linear
num_epochs: 3
Training results
Framework versions
PEFT 0.17.1
Transformers 4.57.1
Pytorch 2.10.0+cu130
Datasets 4.0.0
Tokenizers 0.22.2
