Update README.md

README.md

@@ -19,11 +19,20 @@ This is a pruned version of [openai/whisper-base](https://huggingface.co/openai/
 Pruning was made without any fine-tuning. Method from [this post](https://medium.com/m/global-identity-2?redirectUrl=https%3A%2F%2Ftowardsdatascience.com%2Fhow-to-adapt-a-multilingual-t5-model-for-a-single-language-b9f94f3d9c90) was used.
 
 ## Size
-Only 10% tokens was left: special whisper tokens, added whisper tokens, 100 most popular tokens from tokenizer and 3000 most popular Russian tokens computed by tokenization of russian text corpus.
+Only 10% tokens was left including special whisper tokens, added whisper tokens, 100 most popular tokens from tokenizer and 3000 most popular Russian tokens computed by tokenization of russian text corpus.
+
 Model size is 30%  less then original whisper-base:
 |  | openai/whisper-base | waveletdeboshir/whisper-base-ru-pruned |
 | :------ | :------ | :------ |
 | n of parameters | 74 M | 48.5 M |
 | n of parameters (with proj_out layer) | 99 M | 51 M |
 | model file size | 290 Mb | 203 Mb |
-| vocab_size | 51865 | 4705 |
+| vocab_size | 51865 | 4705 |
+
+## Metrics
+Metrics for this model are on the same level as for openai/whisper-base.
+
+You can fine-tune this model on your data to achive better performance.
+
+## Colab for pruning
+TODO