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--- |
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datasets: |
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- JairamKanna/Tamil-vulnerable-speech |
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language: |
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- ta |
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metrics: |
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- wer |
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library_name: transformers |
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pipeline_tag: automatic-speech-recognition |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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This model is the fine-tuned version of Whisper-large-v2 model for Speech Recognition task for vulnerable individuals in Tamil. |
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#### Preprocessing [optional] |
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#### Training Hyperparameters |
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** training_args = Seq2SeqTrainingArguments( |
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output_dir="./pretrainedwhisper-medium-native-v2", # change to a repo name of your choice |
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per_device_train_batch_size=4, |
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gradient_accumulation_steps=1, # increase by 2x for every 2x decrease in batch size |
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learning_rate=1e-5, |
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warmup_steps=200, |
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max_steps=2000, |
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gradient_checkpointing=True, |
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fp16=True, |
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evaluation_strategy="steps", |
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per_device_eval_batch_size=8, |
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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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optim="adamw_bnb_8bit" |
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) |
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#### Metrics |
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<!-- These are the evaluation metrics being used, ideally with a description of why. --> |
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WER is the evaluation metrics used here. |
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