Wav2Vec2 Base Wolof
This model is a fine-tuned version of facebook/wav2vec2-base on the serge-wilson/wolof_speech_transcription dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2953
- eval_wer: 0.3067
- eval_runtime: 153.1594
- eval_samples_per_second: 14.658
- eval_steps_per_second: 1.835
- epoch: 15.23
- step: 6000
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
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.14.0
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Model tree for serge-wilson/wav2vec-base-wolof
Base model
facebook/wav2vec2-base