Update README.md

README.md

@@ -34,9 +34,9 @@ should probably proofread and complete it, then remove this comment. -->
 # whisper-large-v3-japanese-4k-steps
 
 This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 16.1 dataset. I followed a post by Sanchit Gandhi, https://huggingface.co/blog/fine-tune-whisper
-It took 24 hours using an A100 on Google Colab to complete 4000 steps using the Common Voice 16.1 dataset. Training loss dropped over epochs but WER increased suggesting overfitting. It achieves the following results on the evaluation set:
+It took 24 hours using an A100 on Google Colab to complete 4000 steps using the Common Voice 16.1 dataset. Training loss dropped over epochs but validation loss increased, so textbook overfitting. Furthermore, WER increased. It achieves the following results on the evaluation set:
 - Loss: 0.4057
-- Wer: 1821.4909
+- Wer: 18.2149
 
 ## Model description
 
@@ -71,10 +71,10 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Wer       |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|
-| 0.1374        | 1.02  | 1000 | 0.3618          | 1198.3182 |
-| 0.0508        | 2.04  | 2000 | 0.3658          | 1755.4657 |
-| 0.0206        | 3.05  | 3000 | 0.3904          | 2108.7484 |
-| 0.0066        | 4.07  | 4000 | 0.4057          | 1821.4909 |
+| 0.1374        | 1.02  | 1000 | 0.3618          | 11.983182 |
+| 0.0508        | 2.04  | 2000 | 0.3658          | 17.554657 |
+| 0.0206        | 3.05  | 3000 | 0.3904          | 21.087484 |
+| 0.0066        | 4.07  | 4000 | 0.4057          | 18.214909 |
 
 
 ### Framework versions