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program: train.py
entity: dalle-mini
project: dalle-mini
method: random
metric:
name: eval/loss
goal: minimize
parameters:
learning_rate:
distribution: log_uniform
# from exp(min) to exp(max)
min: -6.9
max: -3.5
gradient_accumulation_steps:
value: 8
warmup_steps:
value: 4000
#TODO: outdated command
command:
- python3
- ${program}
- "--tokenizer_name"
- "boris/dalle-mini-tokenizer"
- "--config_name"
- "facebook/bart-large-cnn"
- "--dataset_repo_or_path"
- "boris/gis_vqgan_f16_16384"
- "--streaming"
- "--use_auth_token"
- "--image_vocab_size"
- 16384
- "--image_length"
- 256
- "--normalize_text"
- True
- "--per_device_train_batch_size"
- 56
- "--per_device_eval_batch_size"
- 56
- "--adafactor"
- "--do_train"
- "--do_eval"
- "--num_train_epochs"
- 1
- "--logging_steps"
- 40
- "--eval_steps"
- 800
- "--output_dir"
- "./output"
- "--overwrite_output_dir"
- "--max_train_samples"
- 10000000
- ${args}
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