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Update README.md

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  1. README.md +4 -4
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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Test WER
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  type: wer
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- value: 30.54
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  ---
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  # Wav2Vec2-Large-XLSR-53-Maltese
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  Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) in Maltese using the [Common Voice](https://huggingface.co/datasets/common_voice)
@@ -41,7 +41,7 @@ import sys
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  model_name = "Akashpb13/xlsr_maltese_wav2vec2"
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  device = "cuda"
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- chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\%\‘\”\�\)\(\*)]'
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  model = Wav2Vec2ForCTC.from_pretrained(model_name).to(device)
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  processor = Wav2Vec2Processor.from_pretrained(model_name)
@@ -70,10 +70,10 @@ def map_to_pred(batch):
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  batch["target"] = batch["sentence"]
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  return batch
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- result = ds.map(map_to_pred, batched=True, batch_size=16, remove_columns=list(ds.features.keys()))
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  wer = load_metric("wer")
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  print(wer.compute(predictions=result["predicted"], references=result["target"]))
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  ```
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- **Test Result**: 30.54 %
 
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  metrics:
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  - name: Test WER
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  type: wer
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+ value: 29.42
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  ---
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  # Wav2Vec2-Large-XLSR-53-Maltese
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  Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) in Maltese using the [Common Voice](https://huggingface.co/datasets/common_voice)
 
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  model_name = "Akashpb13/xlsr_maltese_wav2vec2"
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  device = "cuda"
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+ chars_to_ignore_regex = '[\\,\\?\\.\\!\\-\\;\\:\\"\\“\\%\\‘\\”\\�\\)\\(\\*)]'
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  model = Wav2Vec2ForCTC.from_pretrained(model_name).to(device)
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  processor = Wav2Vec2Processor.from_pretrained(model_name)
 
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  batch["target"] = batch["sentence"]
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  return batch
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+ result = ds.map(map_to_pred, batched=True, batch_size=1, remove_columns=list(ds.features.keys()))
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  wer = load_metric("wer")
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  print(wer.compute(predictions=result["predicted"], references=result["target"]))
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  ```
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+ **Test Result**: 29.42 %