ihanif commited on
Commit
f53d6d6
1 Parent(s): 4898baf

Training in progress, step 100

Browse files
config.json CHANGED
@@ -17,7 +17,7 @@
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  "decoder_layerdrop": 0.0,
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  "decoder_layers": 4,
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  "decoder_start_token_id": 50258,
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- "dropout": 0.0,
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  "encoder_attention_heads": 6,
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  "encoder_ffn_dim": 1536,
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  "encoder_layerdrop": 0.0,
 
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  "decoder_layerdrop": 0.0,
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  "decoder_layers": 4,
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  "decoder_start_token_id": 50258,
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+ "dropout": 0.2,
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  "encoder_attention_heads": 6,
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  "encoder_ffn_dim": 1536,
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  "encoder_layerdrop": 0.0,
pytorch_model.bin CHANGED
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run_1.sh ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ python run_speech_recognition_seq2seq_streaming.py \
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+ --model_name_or_path="openai/whisper-tiny" \
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+ --dataset_name="google/fleurs" \
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+ --dataset_config_name="ps_af" \
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+ --language="pashto" \
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+ --train_split_name="train+validation" \
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+ --eval_split_name="test" \
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+ --model_index_name="Whisper Tiny Pashto" \
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+ --max_steps="200" \
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+ --output_dir="./" \
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+ --per_device_train_batch_size="64" \
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+ --per_device_eval_batch_size="32" \
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+ --gradient_accumulation_steps="1" \
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+ --logging_steps="10" \
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+ --learning_rate="3e-7" \
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+ --warmup_steps="40" \
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+ --evaluation_strategy="steps" \
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+ --eval_steps="100" \
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+ --save_strategy="steps" \
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+ --save_steps="100" \
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+ --generation_max_length="225" \
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+ --length_column_name="input_length" \
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+ --max_duration_in_seconds="30" \
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+ --text_column_name="transcription" \
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+ --freeze_feature_encoder="False" \
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+ --load_best_model_at_end \
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+ --report_to="tensorboard" \
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+ --gradient_checkpointing \
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+ --fp16 \
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+ --overwrite_output_dir="True" \
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+ --do_train \
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+ --do_eval \
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+ --predict_with_generate \
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+ --do_normalize_eval \
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+ --use_auth_token \
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+ --streaming="False" \
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+ --push_to_hub
run_speech_recognition_seq2seq_streaming.py CHANGED
@@ -556,6 +556,7 @@ def main():
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  elif isinstance(train_dataloader.dataset, IterableDataset):
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  train_dataloader.dataset.set_epoch(train_dataloader.dataset._epoch + 1)
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  # Initialize Trainer
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  trainer = Seq2SeqTrainer(
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  model=model,
 
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  elif isinstance(train_dataloader.dataset, IterableDataset):
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  train_dataloader.dataset.set_epoch(train_dataloader.dataset._epoch + 1)
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+ model.config.dropout=0.2
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  # Initialize Trainer
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  trainer = Seq2SeqTrainer(
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  model=model,
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