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LLM-SFT-finetuned-model-randomData – AI Model by nabinadhikariofficial | AlphaNeural AI
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nabinadhikariofficial
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LLM-SFT-finetuned-model-randomData
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transformers
safetensors
qwen2
text-generation
llama-factory
full
generated_from_trainer
conversational
Qwen/Qwen2.5-3B-Instruct
finetune
other
text-generation-inference
endpoints_compatible
us
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nabin_random
This model is a fine-tuned version of
Qwen/Qwen2.5-3B-Instruct
on the random_data 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
distributed_type: multi-GPU
gradient_accumulation_steps: 16
total_train_batch_size: 32
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: 0.03
num_epochs: 3
Training results
Framework versions
Transformers 4.56.2
Pytorch 2.7.1+cu126
Datasets 4.0.0
Tokenizers 0.22.1
