---
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_8.5hr
  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_8.5hr

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: 0.7306
- Wer Ortho: 0.2818
- Wer: 0.2261
- Cer: 0.1004
- Precision: 0.8516
- Recall: 0.8552
- F1: 0.8527

## 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     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:---------:|:------:|:------:|
| 1.0157        | 0.1825 | 100  | 0.9950          | 0.3122    | 0.2683 | 0.1220 | 0.8325    | 0.8364 | 0.8338 |
| 0.8347        | 0.3650 | 200  | 0.8313          | 0.3056    | 0.2562 | 0.1182 | 0.8429    | 0.8450 | 0.8433 |
| 0.6958        | 0.5474 | 300  | 0.7851          | 0.2905    | 0.2393 | 0.1060 | 0.8478    | 0.8503 | 0.8484 |
| 0.8021        | 0.7299 | 400  | 0.7532          | 0.2848    | 0.2286 | 0.1014 | 0.8541    | 0.8563 | 0.8546 |
| 0.8634        | 0.9124 | 500  | 0.7306          | 0.2818    | 0.2261 | 0.1004 | 0.8516    | 0.8552 | 0.8527 |


### Framework versions

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