| #!/usr/bin/env bash |
| set -euo pipefail |
|
|
| cd "$(dirname "$0")/.." |
|
|
| PYTHON_BIN="${PYTHON_BIN:-python}" |
| MODEL_ID="${MODEL_ID:-facebook/mms-1b-all}" |
| TARGET_LANG="${TARGET_LANG:-rmc-script_latin}" |
| OUTPUT_DIR="${OUTPUT_DIR:-artifacts/models/mms-1b-all-romani-adapter-gpu}" |
| EVAL_ROOT="${EVAL_ROOT:-artifacts/evals/mms-1b-all-romani-adapter-gpu}" |
| TRAIN_MANIFEST="${TRAIN_MANIFEST:-artifacts/manifests/clean/train_clean.csv}" |
| VALIDATION_MANIFEST="${VALIDATION_MANIFEST:-artifacts/manifests/clean/validation_clean.csv}" |
| TEST_MANIFEST="${TEST_MANIFEST:-artifacts/manifests/test.csv}" |
| EPOCHS="${EPOCHS:-4}" |
| MAX_STEPS="${MAX_STEPS:-0}" |
| TRAIN_LIMIT="${TRAIN_LIMIT:-0}" |
| VALIDATION_LIMIT="${VALIDATION_LIMIT:-0}" |
| BATCH_SIZE="${BATCH_SIZE:-1}" |
| GRAD_ACCUM="${GRAD_ACCUM:-8}" |
| LEARNING_RATE="${LEARNING_RATE:-1e-3}" |
| WARMUP_STEPS="${WARMUP_STEPS:-25}" |
| EVAL_STEPS="${EVAL_STEPS:-50}" |
| SAVE_ADAPTER_STEPS="${SAVE_ADAPTER_STEPS:-50}" |
| LOGGING_STEPS="${LOGGING_STEPS:-10}" |
| NUM_PROC="${NUM_PROC:-2}" |
| MIXED_PRECISION="${MIXED_PRECISION:-auto}" |
| RUN_EVALS="${RUN_EVALS:-1}" |
|
|
| "${PYTHON_BIN}" - <<'PY' |
| import torch |
|
|
| if not torch.cuda.is_available(): |
| raise SystemExit("CUDA is not available. Select a GPU runtime first.") |
| print("CUDA:", torch.cuda.get_device_name(0)) |
| print("CUDA memory GB:", round(torch.cuda.get_device_properties(0).total_memory / 1024**3, 1)) |
| PY |
|
|
| train_args=( |
| scripts/train_mms_adapter.py |
| --model-id "${MODEL_ID}" |
| --target-lang "${TARGET_LANG}" |
| --train-manifest "${TRAIN_MANIFEST}" |
| --validation-manifest "${VALIDATION_MANIFEST}" |
| --output-dir "${OUTPUT_DIR}" |
| --num-train-epochs "${EPOCHS}" |
| --per-device-train-batch-size "${BATCH_SIZE}" |
| --per-device-eval-batch-size 1 |
| --gradient-accumulation-steps "${GRAD_ACCUM}" |
| --learning-rate "${LEARNING_RATE}" |
| --warmup-steps "${WARMUP_STEPS}" |
| --eval-steps "${EVAL_STEPS}" |
| --save-adapter-steps "${SAVE_ADAPTER_STEPS}" |
| --logging-steps "${LOGGING_STEPS}" |
| --num-proc "${NUM_PROC}" |
| --mixed-precision "${MIXED_PRECISION}" |
| --gradient-checkpointing |
| ) |
|
|
| if [[ "${MAX_STEPS}" != "0" ]]; then |
| train_args+=(--max-steps "${MAX_STEPS}") |
| fi |
| if [[ "${TRAIN_LIMIT}" != "0" ]]; then |
| train_args+=(--train-limit "${TRAIN_LIMIT}") |
| fi |
| if [[ "${VALIDATION_LIMIT}" != "0" ]]; then |
| train_args+=(--validation-limit "${VALIDATION_LIMIT}") |
| fi |
|
|
| "${PYTHON_BIN}" "${train_args[@]}" |
|
|
| ADAPTER_DIR_FOR_EVAL="${OUTPUT_DIR}" |
| PROCESSOR_DIR_FOR_EVAL="${OUTPUT_DIR}/processor" |
| if [[ -f "${OUTPUT_DIR}/best_adapter/adapter.${TARGET_LANG}.safetensors" ]]; then |
| ADAPTER_DIR_FOR_EVAL="${OUTPUT_DIR}/best_adapter" |
| PROCESSOR_DIR_FOR_EVAL="${OUTPUT_DIR}/best_adapter/processor" |
| fi |
|
|
| if [[ "${RUN_EVALS}" != "0" ]]; then |
| "${PYTHON_BIN}" scripts/evaluate_mms_asr.py \ |
| --model-id "${MODEL_ID}" \ |
| --target-lang "${TARGET_LANG}" \ |
| --processor-dir "${PROCESSOR_DIR_FOR_EVAL}" \ |
| --adapter-dir "${ADAPTER_DIR_FOR_EVAL}" \ |
| --manifest "${VALIDATION_MANIFEST}" \ |
| --output-dir "${EVAL_ROOT}/validation-clean" |
|
|
| "${PYTHON_BIN}" scripts/evaluate_mms_asr.py \ |
| --model-id "${MODEL_ID}" \ |
| --target-lang "${TARGET_LANG}" \ |
| --processor-dir "${PROCESSOR_DIR_FOR_EVAL}" \ |
| --adapter-dir "${ADAPTER_DIR_FOR_EVAL}" \ |
| --manifest "${TEST_MANIFEST}" \ |
| --output-dir "${EVAL_ROOT}/test" |
| fi |
|
|
| echo |
| echo "Adapter: ${OUTPUT_DIR}/adapter.${TARGET_LANG}.safetensors" |
| echo "Best/evaluated adapter: ${ADAPTER_DIR_FOR_EVAL}/adapter.${TARGET_LANG}.safetensors" |
| echo "Processor: ${OUTPUT_DIR}/processor" |
| if [[ "${RUN_EVALS}" != "0" ]]; then |
| echo "Validation metrics: ${EVAL_ROOT}/validation-clean/metrics.json" |
| echo "Test metrics: ${EVAL_ROOT}/test/metrics.json" |
| fi |
|
|
