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EDA_md – AI Model by lbyyyyy | AlphaNeural AI
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qwen2.5-32b-verilogcoder-stage2-sft
This model is a fine-tuned version of
/data3/lw/llama-factory/LLaMA-Factory-main/models/qwen2.5-32b-verilogcoder-stage1-v2
on the eda_stage2_v2, the eda_stage2_v2_part2 and the slimorca datasets.
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: 1e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 16
total_train_batch_size: 128
total_eval_batch_size: 64
optimizer: Use adamw_torch_fused 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: 1.0
Training results
Framework versions
Transformers 4.57.1
Pytorch 2.9.1+cu128
Datasets 4.0.0
Tokenizers 0.22.1
