| export HF_PROJECT="t5-base-dutch" | |
| # Variables for training the tokenizer and creating the config | |
| export VOCAB_SIZE="32000" | |
| export N_INPUT_SENTENCES="1000000" # Num of sentences to train the tokenizer | |
| 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="t5-base" # 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_t5_mlm_flax.py \ | |
| --output_dir="${MODEL_PATH}" \ | |
| --model_type="t5" \ | |
| --config_name="${MODEL_PATH}" \ | |
| --tokenizer_name="${MODEL_PATH}" \ | |
| --preprocessing_num_workers="96" \ | |
| --do_train --do_eval \ | |
| --dataset_name="${DATASET}" \ | |
| --dataset_config_name="${DATASET_CONFIG}" \ | |
| --max_seq_length="512" \ | |
| --per_device_train_batch_size="16" \ | |
| --per_device_eval_batch_size="16" \ | |
| --adafactor \ | |
| --learning_rate="0.005" \ | |
| --overwrite_output_dir \ | |
| --num_train_epochs="1" \ | |
| --logging_steps="500" \ | |
| --save_steps="80000" \ | |
| --eval_steps="2500" \ | |
| --weight_decay="0.01" \ | |
| --warmup_steps="10000" \ | |
| --validation_split_count="15000" \ | |
| --push_to_hub | |