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#!/bin/sh
export WANDB_PROJECT="xls-r-basque"
export CUDA_VISIBLE_DEVICES=2
python src/run_speech_recognition_ctc_bnb.py \
--dataset_name="mozilla-foundation/common_voice_8_0" \
--model_name_or_path="facebook/wav2vec2-xls-r-300m" \
--dataset_config_name="eu" \
--output_dir="./" \
--overwrite_output_dir \
--num_train_epochs=100 \
--per_device_train_batch_size=72 \
--per_device_eval_batch_size=72 \
--gradient_accumulation_steps=2 \
--learning_rate=3e-4 \
--save_total_limit=1 \
--warmup_steps=500 \
--evaluation_strategy=steps \
--text_column_name=sentence \
--length_column_name=input_length \
--save_steps=500 \
--eval_steps=500 \
--logging_steps=100 \
--layerdrop=0.0 \
--freeze_feature_encoder \
--feat_proj_dropout=0.1 \
--chars_to_ignore , ? . ! \- \; \: \" “ % ‘ ” � — ’ … – \
--gradient_checkpointing \
--lr_scheduler_type=cosine \
--fp16 \
--group_by_length \
--mask_time_prob=0.1 \
--mask_time_length=10 \
--report_to=wandb \
--run_name="cosine+drop_proj+low_specaugment-300M+cv_8_0" \
--do_train --do_eval \
--use_auth_token --push_to_hub
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