Create run.sh
Browse files
run.sh
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python -m torch.distributed.launch \
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--nproc_per_node=8 \
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run_xtreme_s.py \
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--model_name_or_path="facebook/wav2vec2-xls-r-300m" \
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--task="fleurs-lang_id" \
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--language="all" \
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--output_dir="xtreme_s_xlsr_300m_fleurs_langid" \
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--num_train_epochs=5 \
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--per_device_train_batch_size=8 \
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--per_device_eval_batch_size=1 \
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--gradient_accumulation_steps=1 \
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--learning_rate="3e-4" \
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--warmup_steps=2000 \
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--evaluation_strategy="steps" \
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--max_duration_in_seconds=20 \
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--save_steps=1000 \
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--eval_steps=1000 \
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--logging_steps=1 \
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--layerdrop=0.0 \
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--freeze_feature_encoder \
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--gradient_checkpointing \
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--fp16 \
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--fp16_full_eval \
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--do_train \
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--do_eval \
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--do_predict \
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--metric_for_best_model="accuracy" \
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--greater_is_better=True \
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--load_best_model_at_end \
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--push_to_hub
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