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nl2bash-stack-bugsseq – AI Model by DCAgent2 | AlphaNeural AI | AlphaNeural AI
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nl2bash-stack-bugsseq
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nl2bash-stack-bugsseq
This model was trained from scratch on the None 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: 4e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 16
total_eval_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.98) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 7.0
Training results
Framework versions
Transformers 4.56.1
Pytorch 2.9.1+cu128
Datasets 4.4.1
Tokenizers 0.22.1
