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ARI-Qwen-2.5-7B-q4-AbstRCT – AI Model by EttoreCaputo | AlphaNeural AI
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EttoreCaputo
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ARI-Qwen-2.5-7B-q4-AbstRCT
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unsloth/Qwen2.5-7B-Instruct-unsloth-bnb-4bit
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qwen2.5-7B-q4-my-abstrct
This model is a fine-tuned version of
unsloth/Qwen2.5-7B-Instruct-unsloth-bnb-4bit
on the abstrct 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: 4
total_train_batch_size: 8
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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Framework versions
PEFT 0.12.0
Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 3.2.0
Tokenizers 0.21.0
