dmusingu / luganda_wav2vec2_ctc_train_clean

huggingface.co
Total runs: 3
24-hour runs: -1
7-day runs: -2
30-day runs: -3
Model's Last Updated: February 29 2024
automatic-speech-recognition

Introduction of luganda_wav2vec2_ctc_train_clean

Model Details of luganda_wav2vec2_ctc_train_clean

luganda_wav2vec2_ctc_train_clean

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice_7_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2835
  • Wer: 0.4156
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
5.8861 2.4 500 3.1284 1.0
2.0448 4.81 1000 0.5439 0.7131
0.6342 7.21 1500 0.3713 0.5556
0.4907 9.62 2000 0.3464 0.5015
0.4242 12.02 2500 0.3122 0.4746
0.3898 14.42 3000 0.3164 0.4634
0.357 16.83 3500 0.2896 0.4416
0.3338 19.23 4000 0.2880 0.4409
0.3223 21.63 4500 0.2841 0.4287
0.3072 24.04 5000 0.2849 0.4250
0.2974 26.44 5500 0.2829 0.4194
0.2878 28.85 6000 0.2835 0.4156
Framework versions
  • Transformers 4.38.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.2

Runs of dmusingu luganda_wav2vec2_ctc_train_clean on huggingface.co

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

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luganda_wav2vec2_ctc_train_clean huggingface.co is an AI model on huggingface.co that provides luganda_wav2vec2_ctc_train_clean's model effect (), which can be used instantly with this dmusingu luganda_wav2vec2_ctc_train_clean model. huggingface.co supports a free trial of the luganda_wav2vec2_ctc_train_clean model, and also provides paid use of the luganda_wav2vec2_ctc_train_clean. Support call luganda_wav2vec2_ctc_train_clean model through api, including Node.js, Python, http.

luganda_wav2vec2_ctc_train_clean huggingface.co Url

https://huggingface.co/dmusingu/luganda_wav2vec2_ctc_train_clean

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https://huggingface.co/dmusingu/luganda_wav2vec2_ctc_train_clean

luganda_wav2vec2_ctc_train_clean install

luganda_wav2vec2_ctc_train_clean is an open source model from GitHub that offers a free installation service, and any user can find luganda_wav2vec2_ctc_train_clean on GitHub to install. At the same time, huggingface.co provides the effect of luganda_wav2vec2_ctc_train_clean install, users can directly use luganda_wav2vec2_ctc_train_clean installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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https://huggingface.co/dmusingu/luganda_wav2vec2_ctc_train_clean

Url of luganda_wav2vec2_ctc_train_clean

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