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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} | |