dalle-mini / tools /train /sweep.yaml
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feat(train): update sweep config
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program: train.py
project: dalle-mini
method: random
metric:
name: eval/loss
goal: minimize
parameters:
optim:
value: distributed_shampoo
learning_rate:
distribution: log_uniform
# from exp(min) to exp(max)
min: -9.2
max: -6.9
tokenizer_name:
value: boris/dalle-mini-tokenizer
config_name:
value: ./config/mini
dtype:
value: bfloat16
dataset_repo_or_path:
value: ./data
per_device_train_batch_size:
value: 64
per_device_eval_batch_size:
value: 64
gradient_accumulation_steps:
value: 1
warmup_steps:
value: 1000
num_train_epochs:
value: 1
max_train_samples:
value: 1000000
logging_steps:
value: 40
eval_steps:
value: 200
command:
- python3
- ${program}
- "--streaming"
- "--output_dir"
- "./output"
- "--overwrite_output_dir"
- "--do_train"
- "--do_eval"
- ${args}