Update README.md

README.md

@@ -40,6 +40,10 @@ It achieves the following results on the evaluation set:
 - Wer (without normalization): 15.8969
 - Wer (with normalization): **11.1406**
 
+## Blog post
+
+All information about this model in this blog post: [Speech-to-Text & IA | Transcreva qualquer áudio para o português com o Whisper (OpenAI)... sem nenhum custo!](https://medium.com/@pierre_guillou/speech-to-text-ia-transcreva-qualquer-%C3%A1udio-para-o-portugu%C3%AAs-com-o-whisper-openai-sem-ad0c17384681).
+
 ## New SOTA
 
 The Normalized WER in the [OpenAI Whisper article](https://cdn.openai.com/papers/whisper.pdf) with the [Common Voice 9.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_9_0) test dataset is 16.0. 
@@ -48,18 +52,6 @@ As this test dataset is similar to the [Common Voice 11.0](https://huggingface.c
 
 ![OpenAI results with Whisper Medium and Test dataset of Commons Voice 9.0](https://huggingface.co/pierreguillou/whisper-medium-french/resolve/main/whisper_medium_french_wer_commonvoice9.png)
 
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
 ## Training procedure
 
 ### Training hyperparameters
@@ -85,10 +77,9 @@ The following hyperparameters were used during training:
 | 0.1455        | 0.8   | 4000 | 0.2752          | 16.4597 | 11.8966  |
 | 0.1712        | 1.0   | 5000 | 0.2664          | 15.8969 | 11.1406  |
 
-
 ### Framework versions
 
 - Transformers 4.26.0.dev0
 - Pytorch 1.13.0+cu117
 - Datasets 2.7.1.dev0
-- Tokenizers 0.13.2
+- Tokenizers 0.13.2