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wav2vec doc tweaks (#10808)

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* wording/typos tweaks

* Make model upload instructions simpler
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examples/research_projects/wav2vec2/FINE_TUNE_XLSR_WAV2VEC2.md
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@ -7,7 +7,7 @@ Furthermore, it is very much appreciated if participants fine-tune XLSR-Wav2Vec2
All fine-tuned models uploaded until Friday, the 26th March midnight PST, will be taken into account for competition, and the best model per language will be awarded a prize if the best model performs reasonably well. All fine-tuned models uploaded until Friday, the 26th March midnight PST, will be taken into account for competition, and the best model per language will be awarded a prize if the best model performs reasonably well.
The testing data to evaluate the models will be the official [Common Voice dataset](https://commonvoice.mozilla.org/en/datasets) *`test data`* of version 6.1. Again, participants are very much encouraged to fine-tune XLSR-Wav2Vec2 on languages that are not found in the Common Voice dataset since those languages are even more likely to be underrepresented in the speech community. The testing data to evaluate the models will be the official [Common Voice dataset](https://commonvoice.mozilla.org/en/datasets) *`test data`* of version 6.1. Again, participants are very much encouraged to fine-tune XLSR-Wav2Vec2 on languages that are not found in the Common Voice dataset since those languages are even more likely to be underrepresented in the speech community.
Each model fine-tuned on a language not found in Common Voice, will be evaluated by the Hugging Face after Friday, the 26th March at midnight PST, and if the model performs reasonably well, the model receives a prize as well. Each model fine-tuned on a language not found in Common Voice, will be evaluated by the Hugging Face team after Friday, the 26th March at midnight PST, and if the model performs reasonably well, the model receives a prize as well.
For more information on which data can be used for training, how the models are evaluated exactly, and what type of data preprocessing can be used, please see ["Training and Evaluation Rules"](#training-and-evaluation-rules). For more information on which data can be used for training, how the models are evaluated exactly, and what type of data preprocessing can be used, please see ["Training and Evaluation Rules"](#training-and-evaluation-rules).
**Please keep in mind:** **Please keep in mind:**
@ -136,9 +136,17 @@ To fill...
## How to upload my trained checkpoint ## How to upload my trained checkpoint
To upload your trained checkpoint, make sure to follow the instructions [here](https://huggingface.co/transformers/model_sharing.html) on how to create a model repository on the 🤗 model hub . To upload your trained checkpoint, you have to create a new model repository on the 🤗 model hub, from this page: https://huggingface.co/new
Having created your model repository on the hub, you should clone it locally. > You can also follow the more in-depth instructions [here](https://huggingface.co/transformers/model_sharing.html) if needed.
Having created your model repository on the hub, you should clone it locally:
```bash
git lfs install
git clone https://huggingface.co/username/your-model-name
```
Then and add the following files that fully define a XLSR-Wav2Vec2 checkpoint into the repository. You should have added the following files. Then and add the following files that fully define a XLSR-Wav2Vec2 checkpoint into the repository. You should have added the following files.
@ -186,6 +194,8 @@ datasets:
- common_voice #TODO: remove if you did not use the common voice dataset - common_voice #TODO: remove if you did not use the common voice dataset
- TODO: add more datasets if you have used additional datasets. Make sure to use the exact same - TODO: add more datasets if you have used additional datasets. Make sure to use the exact same
dataset name as the one found [here](https://huggingface.co/datasets). If the dataset can not be found in the official datasets, just give it a new name dataset name as the one found [here](https://huggingface.co/datasets). If the dataset can not be found in the official datasets, just give it a new name
metrics:
- wer
tags: tags:
- audio - audio
- automatic-speech-recognition - automatic-speech-recognition
@ -314,7 +324,7 @@ Your model in then available under *huggingface.co/{your_username}/{your_chosen_
## How to evaluate my trained checkpoint ## How to evaluate my trained checkpoint
Having uploaded your model, you should not evaluate your model in a final step. This should be as simple as Having uploaded your model, you should now evaluate your model in a final step. This should be as simple as
copying the evaluation code of your model card into a python script and running it. Make sure to note copying the evaluation code of your model card into a python script and running it. Make sure to note
the final result on the model card. the final result on the model card.