Example values for finetuning asr
See original GitHub issueHi, congratulations on your achievement in this great work! It is my first time to use fairseq, so could you please give the exact values or an exmple of the parameters in “ASR finetune” training and inference part, which are these values:
DATA_ROOT=
SAVE_DIR=
TRAIN_SET=
VALID_SET=
LABEL_DIR=
BPE_TOKENIZER=
USER_DIR=
PT_CHECKPOINT_PATH=
Thanks a lot! (And the steps that how can get these values would be great!)
Issue Analytics
- State:
- Created a year ago
- Comments:18
Top Results From Across the Web
Fine-Tune Wav2Vec2 for English ASR with Transformers
Using a novel contrastive pretraining objective, Wav2Vec2 learns powerful speech representations from more than 50.000 hours of unlabeled ...
Read more >How to Fine-Tune a Riva ASR Acoustic Model (Citrinet) with ...
ASR Fine-Tuning After the model is trained, evaluated, and there is a need for fine-tuning, the following command can be used to...
Read more >transformers/FINE_TUNE_XLSR_WAV2VEC2.md at main
Pre-process the dataset to input into the model; Run training; Run evaluation. The following examples show how you can launch fine-tuning for the...
Read more >Fine-tuning Whisper ASR models – Weights & Biases - Wandb
Fine-tuning Whisper ASR models ; contents. Returns the contents of the file · The contents of the file ; isNone. Determines if the...
Read more >Fine-Tune XLSR-Wav2Vec2 for low-resource ASR with :câlin
This video will explain in-detail how to fine-tune a multi-lingual Wav2Vec2 model on any dataset of Common Voice. It is a walkthrough of ......
Read more >Top Related Medium Post
No results found
Top Related StackOverflow Question
No results found
Troubleshoot Live Code
Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start FreeTop Related Reddit Thread
No results found
Top Related Hackernoon Post
No results found
Top Related Tweet
No results found
Top Related Dev.to Post
No results found
Top Related Hashnode Post
No results found
Top GitHub Comments
OK, I have read more papers and find out these could be figured out by reading more, very thanks for your reply for these questions! I will shut down this issue, thanks a lot!
okok, let me try try, thanks a lot!