Update README.md

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
        - name: Test CER
          type: cer
-         value: 41.99
+         value: 30.50
 ---
 
 # Wav2Vec2-Large-XLSR-53-Chinese-zh-cn-gpt
@@ -117,7 +117,7 @@ processor = Wav2Vec2Processor.from_pretrained("ydshieh/wav2vec2-large-xlsr-53-ch
 model = Wav2Vec2ForCTC.from_pretrained("ydshieh/wav2vec2-large-xlsr-53-chinese-zh-cn-gpt")
 model.to("cuda")
 
-chars_to_ignore_regex = '[\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\?\\\\\\\\\\\\\\\\.\\\\\\\\\\\\\\\\!\\\\\\\\\\\\\\\\-\\\\\\\\\\\\\\\\;\\\\\\\\\\\\\\\\:"\\\\\\\\\\\\\\\\“\\\\\\\\\\\\\\\\%\\\\\\\\\\\\\\\\‘\\\\\\\\\\\\\\\\”\\\\\\\\\\\\\\\\�\\\\\\\\\\\\\\\\．\\\\\\\\\\\\\\\\⋯\\\\\\\\\\\\\\\\！\\\\\\\\\\\\\\\\－\\\\\\\\\\\\\\\\：\\\\\\\\\\\\\\\\–\\\\\\\\\\\\\\\\。\\\\\\\\\\\\\\\\》\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\）\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\？\\\\\\\\\\\\\\\\；\\\\\\\\\\\\\\\\～\\\\\\\\\\\\\\\\~\\\\\\\\\\\\\\\\…\\\\\\\\\\\\\\\\︰\\\\\\\\\\\\\\\\，\\\\\\\\\\\\\\\\（\\\\\\\\\\\\\\\\」\\\\\\\\\\\\\\\\‧\\\\\\\\\\\\\\\\《\\\\\\\\\\\\\\\\﹔\\\\\\\\\\\\\\\\、\\\\\\\\\\\\\\\\—\\\\\\\\\\\\\\\\／\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\「\\\\\\\\\\\\\\\\﹖\\\\\\\\\\\\\\\\·\\\\\\\\\\\\\\\\×\\\\\\\\\\\\\\\\̃\\\\\\\\\\\\\\\\̌\\\\\\\\\\\\\\\\ε\\\\\\\\\\\\\\\\λ\\\\\\\\\\\\\\\\μ\\\\\\\\\\\\\\\\и\\\\\\\\\\\\\\\\т\\\\\\\\\\\\\\\\─\\\\\\\\\\\\\\\\□\\\\\\\\\\\\\\\\〈\\\\\\\\\\\\\\\\〉\\\\\\\\\\\\\\\\『\\\\\\\\\\\\\\\\』\\\\\\\\\\\\\\\\ア\\\\\\\\\\\\\\\\オ\\\\\\\\\\\\\\\\カ\\\\\\\\\\\\\\\\チ\\\\\\\\\\\\\\\\ド\\\\\\\\\\\\\\\\ベ\\\\\\\\\\\\\\\\ャ\\\\\\\\\\\\\\\\ヤ\\\\\\\\\\\\\\\\ン\\\\\\\\\\\\\\\\・\\\\\\\\\\\\\\\\丶\\\\\\\\\\\\\\\\ａ\\\\\\\\\\\\\\\\ｂ\\\\\\\\\\\\\\\\ｆ\\\\\\\\\\\\\\\\ｇ\\\\\\\\\\\\\\\\ｉ\\\\\\\\\\\\\\\\ｎ\\\\\\\\\\\\\\\\ｐ\\\\\\\\\\\\\\\\ｔ' + "\\\\\\\\\\\\\\\\']"
+chars_to_ignore_regex = '[\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\?\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\.\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\!\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\-\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\;\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\:"\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\“\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\%\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\‘\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\”\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\�\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\．\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\⋯\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\！\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\－\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\：\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\–\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\。\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\》\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\）\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\？\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\；\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\～\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\~\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\…\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\︰\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\，\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\（\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\」\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\‧\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\《\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\﹔\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\、\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\—\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\／\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\「\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\﹖\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\·\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\×\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\̃\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\̌\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ε\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\λ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\μ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\и\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\т\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\─\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\□\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\〈\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\〉\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\『\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\』\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ア\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\オ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\カ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\チ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ド\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ベ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ャ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ヤ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ン\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\・\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\丶\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ａ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ｂ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ｆ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ｇ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ｉ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ｎ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ｐ\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ｔ' + "\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\']"
 
 resampler = torchaudio.transforms.Resample(48_000, 16_000)
 
@@ -148,7 +148,7 @@ result = test_dataset.map(evaluate, batched=True, batch_size=8)
 print("CER: {:2f}".format(100 * chunked_cer(predictions=result["pred_strings"], targets=result["sentence"], chunk_size=1000)))
 ```
 
-**Test Result**: 41.987498 %
+**Test Result**: 30.497816 %
 
 
 ## Training