Downloads · 30 days
2
2% of all-time downloads
data_seed_bs64_1_wav2vec2-large-xlsr-53-buckeye-ipa
ginic/data_seed_bs64_1_wav2vec2-large-xlsr-53-buckeye-ipa
data_seed_bs64_1_wav2vec2-large-xlsr-53-buckeye-ipa is a automatic speech recognition model from ginic. Use it when you need speech turned into text. The card lists the license as mit.
This model was created to support experiments for evaluating phonetic transcription with the Buckeye corpus as part of https://github.com/ginic/multipa. This is a version of facebook/wav2vec2-large-xlsr-53 fine tuned…
All-time downloads
104
Public
Parameters
316M
1.3 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.3 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- License
- mit
- Model type
- wav2vec2
- Access
- Public
- Created
- Aug 25, 2025
- Updated
- Aug 25, 2025
- SHA
- 5d4c4837
Model card
From the Hugging Face model README
About
This model was created to support experiments for evaluating phonetic transcription with the Buckeye corpus as part of https://github.com/ginic/multipa. This is a version of facebook/wav2vec2-large-xlsr-53 fine tuned on a specific subset of the Buckeye corpus. For details about specific model parameters, please view the config.json here or training scripts in the scripts/buckeye_experiments folder of the GitHub repository.
Experiment Details
Vary the random seed to select training data while keeping an even 50/50 gender split to measure statistical significance of changing training data selection. Retrain with the same model parameters, but different data seeding to measure statistical significance of data seed, keeping 50/50 gender split.
Goals:
- Establish whether data variation with the same gender makeup is statistically significant in changing performance on the test set
Params to vary:
- training data seed (--train_seed): [91, 114, 771, 503]
- Task
- Automatic Speech Recognition
- Type
- wav2vec2
- License
- mit
- Languages
- en
- Created
- Aug 25, 2025
- Updated
- Aug 25, 2025