almost state of the art

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
        - name: Test WER
          type: wer
-         value: 81.73
+         value: 69.63
 ---
 # Wav2Vec2-Large-XLSR-53-Assamese
 Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Assamese using the [Common Voice](https://huggingface.co/datasets/common_voice).
@@ -91,6 +91,6 @@ def evaluate(batch):
 result = test_dataset.map(evaluate, batched=True, batch_size=8)
 print("WER: {:2f}".format(100 * wer.compute(predictions=result["pred_strings"], references=result["sentence"])))
 ```
-**Test Result**: 81.73 % 
+**Test Result**: 69.63 % 
 ## Training
-The Common Voice `train` and `validation` datasets were used for training.
+The Common Voice `train` and `validation` datasets were used for training.