Wer is very low.
{
  "train_loss": 8.534393310546875,
  "learning_rate": 0.00012372159108053893,
  "global_step": 5610,
  "train_backward_timing in s": 0.15601778030395508,
  "train_step_timing in s": 0.34882450103759766,
  "training_batch_wer": 0.18061673641204834,
  "epoch": 30,
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  "_timestamp": 1712744688.4421802,
  "_runtime": 11167.270045042038,
  "_step": 293353,
  "validation_step_timing in s": 0.02845907211303711,
  "val_loss": 6.631827354431152,
  "val_wer": 0.12062931060791016,
  "test_step_timing in s": 0.043920040130615234,
  "test_loss": 10.514272689819336,
  "test_wer": 0.17779342830181122,
  "_wandb": {
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  } i used common voice13 hindi as dataset
 my issue is that wer for the model i used i.e conformer_large_ctc is very low .what could be the reason for such a low wer.
@titu1994 sir I'm confused, the metric is "word error rate" - it's good if it's low. Ideal wer is 0 actually i was worried about overfitting of data btw thanks sir 🙌 This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days. This issue was closed because it has been inactive for 7 days since being marked as stale.
conf:

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```[tasklist]
### Tasks
- [ ] Add a draft title or issue reference here
```


