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# wav2vec2-base-igbo

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9388
- Wer Ortho: 145.8015
- Wer: 145.4198
- Accuracy: 0.0
- F1: 0.0
- Recall: 0.0

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer      | Accuracy | F1  | Recall |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:--------:|:--------:|:---:|:------:|
| 0.0004        | 50.0  | 500  | 2.9388          | 145.8015  | 145.4198 | 0.0      | 0.0 | 0.0    |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer", "accuracy", "f1", "recall"], "base_model": "openai/whisper-small", "model-index": [{"name": "wav2vec2-base-igbo", "results": []}]}
transformers pytorch whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us