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Qwen2.5-Coder-14B-verilog – AI Model by tsbthu | AlphaNeural AI
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Qwen2.5-Coder-14B-verilog
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20250529_143802
This model is a fine-tuned version of
/mnt/public/models/Qwen2.5-Coder-14B-Instruct
on the verilog 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-06
train_batch_size: 2
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 8
total_train_batch_size: 64
total_eval_batch_size: 32
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_steps: 2000
num_epochs: 3.0
Training results
Framework versions
PEFT 0.15.1
Transformers 4.51.3
Pytorch 2.7.0+cu126
Datasets 3.5.0
Tokenizers 0.21.1
