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rag_classic_reasoning – AI Model by matyaydin | AlphaNeural AI
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rag_classic_reasoning
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transformers
safetensors
qwen3
text-generation
generated_from_trainer
conversational
Qwen/Qwen3-0.6B-Base
finetune
apache-2.0
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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rag_classic_reasoning
This model is a fine-tuned version of
Qwen/Qwen3-0.6B-Base
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: 4e-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 4
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: linear
num_epochs: 1
Training results
Framework versions
Transformers 4.51.3
Pytorch 2.7.0+cu126
Datasets 3.2.0
Tokenizers 0.21.0
