export HF_PROJECT="gpt2-large-dutch-2" | |
# Variables for training the tokenizer and creating the config | |
export VOCAB_SIZE="50257" | |
export DATASET="yhavinga/mc4_nl_cleaned" # Name of the dataset in the Huggingface Hub | |
export DATASET_CONFIG="full" # Config of the dataset in the Huggingface Hub | |
export DATASET_SPLIT="train" # Split to use for training tokenizer and model | |
export TEXT_FIELD="text" # Field containing the text to be used for training | |
export CONFIG_TYPE="gpt2-large" # Config that our model will use | |
export MODEL_PATH="${HOME}/data/${HF_PROJECT}" # Path to the model, e.g. here inside the mount | |
python run_clm_flax.py \ | |
--output_dir="${MODEL_PATH}" \ | |
--model_type="gpt2" \ | |
--config_name="${MODEL_PATH}" \ | |
--model_name_or_path="${MODEL_PATH}" \ | |
--tokenizer_name="${MODEL_PATH}" \ | |
--preprocessing_num_workers="96" \ | |
--do_train --do_eval \ | |
--dataset_name="${DATASET}" \ | |
--dataset_config_name="${DATASET_CONFIG}" \ | |
--block_size="512" \ | |
--per_device_train_batch_size="4" \ | |
--per_device_eval_batch_size="4" \ | |
--learning_rate="0.000033" --warmup_steps="5000" \ | |
--adafactor \ | |
--overwrite_output_dir \ | |
--num_train_epochs="1" \ | |
--logging_steps="500" \ | |
--save_steps="20000" \ | |
--eval_steps="2500" | |
# \ | |
# --push_to_hub | |
# --adam_beta1="0.9" --adam_beta2="0.98" --weight_decay="0.01" \ | |