fix typos

README.md

@@ -31,20 +31,20 @@ model-index:
 
 Bem-vindo ao whisper medium para transcrição em português 👋🏻
 
-If you are looking to **quickly**, and **reliably**, transcribe portuguese audio to text, you are in the right place!
+If you are looking to **quickly**, and **reliably**, transcribe Portuguese audio to text, you are in the right place!
 
-With a state-of-the-art [Word Error Rate](https://huggingface.co/spaces/evaluate-metric/wer) (WER) of just **6.58** in Common Voice 11, this model shows increases in precision of more than **x2** compared to past state of the art [wav2vec2](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese) models. When compared to the original [whisper-medium](https://huggingface.co/openai/whisper-medium) model it shows a **x1.2** improvement 🚀. 
+With a state-of-the-art [Word Error Rate](https://huggingface.co/spaces/evaluate-metric/wer) (WER) of just **6.579** in Common Voice 11, this model offers an **x2** precision increase compared to prior state-of-the-art [wav2vec2](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese) models. Compared to the original [whisper-medium](https://huggingface.co/openai/whisper-medium) model it delivers an **x1.2** improvement 🚀. 
 
 This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the [mozilla-foundation/common_voice_11](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0) dataset. 
 
-The following table shows a **comparison** between the results of our model and those achieved by the most downloaded models in the hub for portuguese Automatic Speech Recognition:
+The following table displays a **comparison** between the results of our model and those achieved by the most downloaded models in the hub for [Portuguese Automatic Speech Recognition](https://huggingface.co/models?language=pt&pipeline_tag=automatic-speech-recognition&sort=downloads) 🗣:
 
 | Model                                            | WER    | Parameters |
 |--------------------------------------------------|:--------:|:------------:|
-| [openai/whisper-medium](https://huggingface.co/openai/whisper-medium)                            | 8.10   | 769M       |
-| [jlondonobo/whisper-medium-pt](https://huggingface.co/jlondonobo/whisper-medium-pt)                     | **6.58** 🤗  | 769M       |
-| [jonatasgrosman/wav2vec2-large-xlsr-53-portuguese](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese) | 11.31  | 317M       |
-| [Edresson/wav2vec2-large-xlsr-coraa-portuguese](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese)    | 20.08 | 317M       |
+| [openai/whisper-medium](https://huggingface.co/openai/whisper-medium)                            | 8.100   | 769M       |
+| [jlondonobo/whisper-medium-pt](https://huggingface.co/jlondonobo/whisper-medium-pt)                     | **6.579** 🤗  | 769M       |
+| [jonatasgrosman/wav2vec2-large-xlsr-53-portuguese](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese) | 11.310  | 317M       |
+| [Edresson/wav2vec2-large-xlsr-coraa-portuguese](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese)    | 20.080 | 317M       |
 
 
 ### Training hyperparameters
@@ -63,11 +63,11 @@ We used the following hyperparameters for training:
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.0698        | 1.09  | 1000 | 0.1876          | 7.1889 |
-| 0.0218        | 3.07  | 2000 | 0.2254          | 7.1098 |
-| 0.0053        | 5.06  | 3000 | 0.2711          | 6.9686 |
-| 0.0017        | 7.04  | 4000 | 0.3030          | 6.6862 |
-| 0.0005        | 9.02  | 5000 | 0.3205          | **6.5786** 🤗 |
+| 0.0698        | 1.09  | 1000 | 0.1876          | 7.189 |
+| 0.0218        | 3.07  | 2000 | 0.2254          | 7.110 |
+| 0.0053        | 5.06  | 3000 | 0.2711          | 6.969 |
+| 0.0017        | 7.04  | 4000 | 0.3030          | 6.686 |
+| 0.0005        | 9.02  | 5000 | 0.3205          | **6.579** 🤗 |
 
 
 ### Framework versions