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63 lines
1.9 KiB
63 lines
1.9 KiB
#!/bin/bash
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usage="$(basename "$0") [-d <data-split-name>]
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Argument -d takes (few-shot) data split names.
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Possible data-split names : 50-dpd|100-dpd|125-dpd|250-dpd"
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while getopts :d: flag
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do
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case "${flag}" in
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d) data_split=${OPTARG};;
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:) printf "missing argument for -%s\n" "$OPTARG" >&2; echo "$usage" >&2; exit 1;;
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esac
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done
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# check for mandatory/required -d argument
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# mandatory arguments
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if [ ! "$data_split" ]; then
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echo "arguments -d must be provided"
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echo "$usage" >&2; exit 1
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fi
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# Check whether the required environment vars are set
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if [ -z "${SAVED_MODELS_PROMPT}" ]; then
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echo "Must set SAVED_MODELS_PROMPT in environment, run set_env.sh first!";
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exit 1
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fi
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# Check whether the required environment vars are set
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if [ -z "${PRE_TRAINED_SOLOIST}" ]; then
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echo "Pre-trained SOLOIST Model path must be provided!";
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echo "Must set PRE_TRAINED_SOLOIST in environment, run set_env.sh first!";
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exit 1
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fi
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# check if the training data file exists
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TRAIN_DATA_FILE=../data/prompt-learning/"${data_split}"/train.soloist.json
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if [ -f "$TRAIN_DATA_FILE" ]; then
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echo "Selected Training set :: ${data_split}/train.soloist.json"
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else
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echo "Training File with set ${data_split} does not exist."
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exit 1
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fi
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# create experiment folder for storing saved models
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datetime_now=$(date +"%Y%m%dT%H%M%S")
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experiment_folder="${data_split}"/experiment-${datetime_now}
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SAVE_DIR="${SAVED_MODELS_PROMPT}"/"${experiment_folder}"
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echo "Trained Models (epochs) will be saved in ${SAVE_DIR}"
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# different number of epoch for different training sets
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# when using prompt ensemble for training, preferably use more number of epochs.
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epochs=5
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python prompt_train.py \
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--save_model_dir="${SAVE_DIR}" \
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--pretrained_model_path="${PRE_TRAINED_SOLOIST}" \
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--train_data_file="${TRAIN_DATA_FILE}" \
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--validation_file=../data/prompt-learning/valid/valid.soloist.json \
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--num_epochs $epochs \
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--learning_rate 5e-5 \
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--with_inverse_prompt \
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--inverse_prompt_weight 0.3 |