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single-node-single-gpu-qwen-custom-sft – AI Model by sravanthib | AlphaNeural AI
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single-node-single-gpu-qwen-custom-sft
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peft
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Qwen/Qwen2.5-3B
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single-node-single-gpu-qwen-custom-sft
This model is a fine-tuned version of
Qwen/Qwen2.5-3B
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: 0.0001
train_batch_size: 2
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
gradient_accumulation_steps: 10
total_train_batch_size: 20
optimizer: Use 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: 0.05
training_steps: 500
Training results
Framework versions
PEFT 0.14.0
Transformers 4.51.3
Pytorch 2.3.0+cu121
Datasets 2.15.0
Tokenizers 0.21.2
