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# finetuning-wav2vec-large-swahili-asr-model_v19

This model is a fine-tuned version of [Joshua-Abok/finetuning-wav2vec-large-swahili-asr-model_v10](https://huggingface.co/Joshua-Abok/finetuning-wav2vec-large-swahili-asr-model_v10) on the fleurs dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.3234
- eval_wer: 0.9985
- eval_runtime: 63.1279
- eval_samples_per_second: 7.714
- eval_steps_per_second: 0.966
- epoch: 9.73
- step: 2000

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 40
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["fleurs"], "base_model": "Joshua-Abok/finetuning-wav2vec-large-swahili-asr-model_v10", "model-index": [{"name": "finetuning-wav2vec-large-swahili-asr-model_v19", "results": []}]}
transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer dataset:fleurs base_model:Joshua-Abok/finetuning-wav2vec-large-swahili-asr-model_v10 license:apache-2.0 endpoints_compatible region:us