---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- sawadogosalif/MooreFRCollectionsAudios
metrics:
- wer
model-index:
- name: SaCHi_ASR
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: sawadogosalif/MooreFRCollectionsAudios
      type: sawadogosalif/MooreFRCollectionsAudios
      args: 'config: train, split: train'
    metrics:
    - name: Wer
      type: wer
      value: 21.311061768268065
---

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

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the sawadogosalif/MooreFRCollectionsAudios dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2234
- Wer: 21.3111

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.4253        | 0.4657 | 400  | 0.4046          | 34.3409 |
| 0.2789        | 0.9313 | 800  | 0.2871          | 24.3238 |
| 0.2239        | 1.3970 | 1200 | 0.2498          | 19.3530 |
| 0.2122        | 1.8626 | 1600 | 0.2270          | 23.5416 |
| 0.1209        | 2.3283 | 2000 | 0.2234          | 21.3111 |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1