---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
- precision
- recall
- f1
model-index:
- name: ./whisper-base-ea_base
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# ./whisper-base-ea_base

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Afrispeech-200 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6880
- Wer Ortho: 0.2755
- Wer: 0.2202
- Cer: 0.0998
- Precision: 0.8628
- Recall: 0.8622
- F1: 0.8616

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer    | Cer    | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:---------:|:------:|:------:|
| 0.9241        | 0.4237 | 100  | 0.8794          | 0.2973    | 0.2468 | 0.1060 | 0.8428    | 0.8469 | 0.8443 |
| 0.7528        | 0.8475 | 200  | 0.7464          | 0.2903    | 0.2354 | 0.1032 | 0.8583    | 0.8593 | 0.8581 |
| 0.5275        | 1.2712 | 300  | 0.7158          | 0.2778    | 0.2285 | 0.1000 | 0.8619    | 0.8627 | 0.8616 |
| 0.5686        | 1.6949 | 400  | 0.6956          | 0.2805    | 0.2255 | 0.1021 | 0.8638    | 0.8632 | 0.8626 |
| 0.3472        | 2.1186 | 500  | 0.6880          | 0.2755    | 0.2202 | 0.0998 | 0.8628    | 0.8622 | 0.8616 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1