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XCoder-Complexity-Scorer – AI Model by banksy235 | AlphaNeural AI
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XCoder-Complexity-Scorer
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code_complexity
This model is a fine-tuned version of
Meta-Llama-3-8B-Instruct
on the 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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 128
total_eval_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1.0
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.39.0
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2
