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full_dataset_weighted_2.5-7B__2025-04 – AI Model by thomas-erhart | AlphaNeural AI
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thomas-erhart
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full_dataset_weighted_2.5-7B__2025-04
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peft
safetensors
llama-factory
lora
unsloth
generated_from_trainer
unsloth/Qwen2.5-7B
adapter
apache-2.0
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full_dataset_weighted_2.5-7B__2025-04
This model is a fine-tuned version of
Qwen/Qwen2.5-7B
on the my_train_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: 0.0001
train_batch_size: 8
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
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
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Framework versions
PEFT 0.15.0
Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 3.3.2
Tokenizers 0.21.0
