SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

[XLSR-Wav2Vec2 Info doc] Add a couple of lines (#10806)

Browse Source 
* finish

* fix

* fix

* fix

* fix
This commit is contained in:
Patrick von Platen
2021-03-19 12:52:54 +03:00
committed by GitHub
parent 117dba9948
commit e8968bd03a
1 changed files with 14 additions and 10 deletions
Download Patch File Download Diff File Expand all files Collapse all files

24
examples/research_projects/wav2vec2/FINE_TUNE_XLSR_WAV2VEC2.md
View File

@@ -22,15 +22,16 @@ It is very much possible that prizes will be given to groups of people instead o
- [Organization of the fine tuning week](#organization-of-the-fine-tuning-week)
- [How to fine tune XLSR Wav2Vec2](#how-to-fine-tune-xlsr-wav2vec2)
- [Google colab setup](#google-colab-setup)
- [Local machine](#local-machine)
- [Google colab setup](#google-colab-setup)
- [Local machine](#local-machine)
- [How to upload my trained checkpoint](#how-to-upload-my-trained-checkpoint)
- [How to create the README](#how-to-create-the-README)
- [How to create the README](#how-to-create-the-readme)
- [How to evaluate my trained checkpoint](#how-to-evaluate-my-trained-checkpoint)
- [Rules of training and evaluation](#rules-of-training-and-evaluation)
- [Tips and tricks for training](#tips-and-tricks-for-training)
- [Tips and tricks](#tips-and-tricks)
- [How to combine multiple datasests into one](#how-to-combine-multiple-datasets-into-one)
- [How to effectively preprocess the data](#how-to-effectively-preprocess-the-data)
- [How to efficiently preproces the data](#how-to-do-efficiently-load-datasets-with-limited-ram-and-hard-drive-space)
- [How to do hyperparameter tuning](#how-to-do-hyperparameter-tuning)
- [How to preprocess and evaluate character based languages](#how-to-preprocess-and-evaluate-character-based-languages)
- [Further reading material](#further-reading-material)
@@ -284,7 +285,7 @@ result = test_dataset.map(evaluate, batched=True, batch_size=8)
print("WER: {:2f}".format(100 * wer.compute(predictions=result["pred_strings"], references=result["sentence"])))
```
**Result**: XX.XX % # TODO: write output of print here
**Test Result**: XX.XX % # TODO: write output of print here
## Training
@@ -325,23 +326,26 @@ done, *e.g.* [here](https://discuss.huggingface.co/t/spanish-asr-fine-tuning-wav
## Tips and tricks
TODO...
This section summarizes a couple of tips and tricks across various topics. It will continously be updated during the week.
### How to combine multiple datasets into one
Check out [this](https://discuss.huggingface.co/t/how-to-combine-local-data-files-with-an-official-dataset/4685) post.
### How to effectively preprocess the data
### How to do hyperparameter turing for my language
### How to do efficiently load datasets with limited ram and hard drive space
Check out [this](https://discuss.huggingface.co/t/german-asr-fine-tuning-wav2vec2/4558/8?u=patrickvonplaten) post.
### How to do hyperparameter tuning
### How to preprocess and evaluate character based languages
### How to do lazy data loading
## Further reading material
It is recommended that take some time to read up on how Wav2vec2 works in theory.