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mugi-qwen2.5-7b-lora – AI Model by Psycube | AlphaNeural AI
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Psycube
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mugi-qwen2.5-7b-lora
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peft
safetensors
qwen2
text-generation
adapter
llama-factory
lora
transformers
conversational
Qwen/Qwen2.5-7B-Instruct
other
text-generation-inference
endpoints_compatible
us
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Model card
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train_2026-08-03-16-24-00
This model is a fine-tuned version of
Qwen/Qwen2.5-7B-Instruct
on the mugi_dataset 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: 5e-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
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
num_epochs: 3.0
Training results
Framework versions
PEFT 0.18.1
Transformers 5.8.0
Pytorch 2.11.0+cu130
Datasets 4.0.0
Tokenizers 0.22.2
