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@@ -31,7 +31,7 @@ should probably proofread and complete it, then remove this comment. -->
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  # Whisper Small Da - WasuratS
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- This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.6393
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  - Wer Ortho: 29.0926
@@ -62,34 +62,6 @@ The following hyperparameters were used during training:
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  - training_steps: 4000
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  - mixed_precision_training: Native AMP
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- ``` %python
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- from transformers import Seq2SeqTrainingArguments
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-
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- training_args = Seq2SeqTrainingArguments(
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- output_dir="./whisper-small-da",
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- per_device_train_batch_size=16,
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- gradient_accumulation_steps=1,
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- learning_rate=1e-5,
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- lr_scheduler_type="linear",
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- warmup_steps=50,
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- max_steps=4000,
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- gradient_checkpointing=True,
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- fp16=True,
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- fp16_full_eval=True,
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- evaluation_strategy="steps",
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- per_device_eval_batch_size=16,
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- predict_with_generate=True,
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- generation_max_length=225,
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- save_steps=500,
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- eval_steps=500,
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- logging_steps=25,
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- report_to=["tensorboard"],
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- load_best_model_at_end=True,
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- metric_for_best_model="wer",
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- greater_is_better=False,
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- push_to_hub=True,
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- )
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- ```
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  ### Training results
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  # Whisper Small Da - WasuratS
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset on Danish language
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  It achieves the following results on the evaluation set:
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  - Loss: 0.6393
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  - Wer Ortho: 29.0926
 
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  - training_steps: 4000
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  - mixed_precision_training: Native AMP
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  ### Training results
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