Recalculate metrics on the whole dataset

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
        - name: Test WER
          type: wer
-         value: 18.44
+         value: 17.39
 ---
 
 # Wav2Vec2-Large-XLSR-53-Russian
@@ -59,7 +59,7 @@ test_dataset = test_dataset.map(speech_file_to_array_fn)
 inputs = processor(test_dataset["speech"][:2], sampling_rate=16_000, return_tensors="pt", padding=True)
 
 with torch.no_grad():
-\\tlogits = model(inputs.input_values, attention_mask=inputs.attention_mask).logits
+\\\\tlogits = model(inputs.input_values, attention_mask=inputs.attention_mask).logits
 
 predicted_ids = torch.argmax(logits, dim=-1)
 
@@ -95,7 +95,7 @@ processor = Wav2Vec2Processor.from_pretrained("anton-l/wav2vec2-large-xlsr-53-ru
 model = Wav2Vec2ForCTC.from_pretrained("anton-l/wav2vec2-large-xlsr-53-russian")
 model.to("cuda")
 
-cv_test = pd.read_csv("cv-corpus-6.1-2020-12-11/ru/test.tsv", sep='\t')
+cv_test = pd.read_csv("cv-corpus-6.1-2020-12-11/ru/test.tsv", sep='\\t')
 clips_path = "cv-corpus-6.1-2020-12-11/ru/clips/"
 
 def clean_sentence(sent):
@@ -135,7 +135,7 @@ del cv_test
 print("WER: {:2f}".format(100 * wer.compute(predictions=preds, references=targets)))
 ```
 
-**Test Result**: 18.44 %  
+**Test Result**: 17.39 %  
 
 
 ## Training