finetuning-wav2vec-large-swahili-asr-model_v10
This model is a fine-tuned version of Joshua-Abok/finetuned_wav2vec_asr on the common_voice_12_0 dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.3257
- eval_wer: 0.1481
- eval_runtime: 611.0298
- eval_samples_per_second: 17.966
- eval_steps_per_second: 2.247
- epoch: 14.79
- step: 20000
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for Adeptschneider/wav2vec-large-swahili-asr-model-with-swahili-language-model
Base model
AntonyG/fine-tune-wav2vec2-large-xls-r-1b-sw
Finetuned
Joshua-Abok/finetuned_wav2vec_asr