---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wisper-small-malagasy
  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. -->

# wisper-small-malagasy

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8951
- Wer: 0.4742

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 1.3904        | 8.1983  | 500  | 0.6457          | 0.4847 |
| 0.0285        | 16.3967 | 1000 | 0.7599          | 0.4859 |
| 0.0038        | 24.5950 | 1500 | 0.7853          | 0.4771 |
| 0.0008        | 32.7934 | 2000 | 0.8225          | 0.4738 |
| 0.0003        | 40.9917 | 2500 | 0.8441          | 0.4738 |
| 0.0002        | 49.1818 | 3000 | 0.8617          | 0.4754 |
| 0.0002        | 57.3802 | 3500 | 0.8751          | 0.4758 |
| 0.0002        | 65.5785 | 4000 | 0.8857          | 0.4746 |
| 0.0001        | 73.7769 | 4500 | 0.8922          | 0.4734 |
| 0.0001        | 81.9752 | 5000 | 0.8951          | 0.4742 |


### Framework versions

- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 2.18.0
- Tokenizers 0.21.2