transformers pytorch whisper automatic-speech-recognition generated_from_trainer multilingual base_model:openai/whisper-base license:apache-2.0 endpoints_compatible region:us
---
language:
- multilingual
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Base Wolof
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Base Wolof

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2902
- Wer: 32.8385

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5632        | 1.14  | 1000 | 0.4672          | 48.8263 |
| 0.3464        | 2.29  | 2000 | 0.3461          | 34.6403 |
| 0.2514        | 3.43  | 3000 | 0.3013          | 32.1406 |
| 0.1957        | 4.57  | 4000 | 0.2902          | 32.8385 |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.13.3
