dmusingu / luganda_wav2vec2_ctc_tokenizer

huggingface.co
Total runs: 11
24-hour runs: -2
7-day runs: -1
30-day runs: 10
Model's Last Updated: February 22 2024
automatic-speech-recognition

Introduction of luganda_wav2vec2_ctc_tokenizer

Model Details of luganda_wav2vec2_ctc_tokenizer

luganda_wav2vec2_ctc_tokenizer

This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice_7_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5588
  • Wer: 0.5609
Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 30
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Wer
4.1365 2.4 500 1.9598 1.0
0.5695 4.81 1000 0.5853 0.7329
0.176 7.21 1500 0.5381 0.6747
0.0845 9.62 2000 0.5128 0.6270
0.0424 12.02 2500 0.4651 0.6014
0.0127 14.42 3000 0.5395 0.6049
-0.0063 16.83 3500 0.5169 0.5842
-0.0212 19.23 4000 0.4990 0.5833
-0.0336 21.63 4500 0.5318 0.5680
-0.0424 24.04 5000 0.5465 0.5702
-0.0495 26.44 5500 0.5541 0.5637
-0.0565 28.85 6000 0.5588 0.5609
Framework versions
  • Transformers 4.37.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2

Runs of dmusingu luganda_wav2vec2_ctc_tokenizer on huggingface.co

11
Total runs
-2
24-hour runs
-2
3-day runs
-1
7-day runs
10
30-day runs

More Information About luganda_wav2vec2_ctc_tokenizer huggingface.co Model

More luganda_wav2vec2_ctc_tokenizer license Visit here:

https://choosealicense.com/licenses/apache-2.0

luganda_wav2vec2_ctc_tokenizer huggingface.co

luganda_wav2vec2_ctc_tokenizer huggingface.co is an AI model on huggingface.co that provides luganda_wav2vec2_ctc_tokenizer's model effect (), which can be used instantly with this dmusingu luganda_wav2vec2_ctc_tokenizer model. huggingface.co supports a free trial of the luganda_wav2vec2_ctc_tokenizer model, and also provides paid use of the luganda_wav2vec2_ctc_tokenizer. Support call luganda_wav2vec2_ctc_tokenizer model through api, including Node.js, Python, http.

luganda_wav2vec2_ctc_tokenizer huggingface.co Url

https://huggingface.co/dmusingu/luganda_wav2vec2_ctc_tokenizer

dmusingu luganda_wav2vec2_ctc_tokenizer online free

luganda_wav2vec2_ctc_tokenizer huggingface.co is an online trial and call api platform, which integrates luganda_wav2vec2_ctc_tokenizer's modeling effects, including api services, and provides a free online trial of luganda_wav2vec2_ctc_tokenizer, you can try luganda_wav2vec2_ctc_tokenizer online for free by clicking the link below.

dmusingu luganda_wav2vec2_ctc_tokenizer online free url in huggingface.co:

https://huggingface.co/dmusingu/luganda_wav2vec2_ctc_tokenizer

luganda_wav2vec2_ctc_tokenizer install

luganda_wav2vec2_ctc_tokenizer is an open source model from GitHub that offers a free installation service, and any user can find luganda_wav2vec2_ctc_tokenizer on GitHub to install. At the same time, huggingface.co provides the effect of luganda_wav2vec2_ctc_tokenizer install, users can directly use luganda_wav2vec2_ctc_tokenizer installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

luganda_wav2vec2_ctc_tokenizer install url in huggingface.co:

https://huggingface.co/dmusingu/luganda_wav2vec2_ctc_tokenizer

Url of luganda_wav2vec2_ctc_tokenizer

luganda_wav2vec2_ctc_tokenizer huggingface.co Url

Provider of luganda_wav2vec2_ctc_tokenizer huggingface.co

dmusingu
ORGANIZATIONS

Other API from dmusingu

huggingface.co

Total runs: 0
Run Growth: 0
Growth Rate: 0.00%
Updated:June 06 2026
huggingface.co

Total runs: 0
Run Growth: 0
Growth Rate: 0.00%
Updated:June 06 2026