---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: openai/whisper-small
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fleurs
      type: fleurs
      config: ps_af
      split: test
      args: ps_af
    metrics:
    - name: Wer
      type: wer
      value: 66.00332929782083
---

<!-- 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. -->

# openai/whisper-small

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0277
- Wer: 66.0033

## 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: 3e-07
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.0871        | 14.29  | 100  | 2.0102          | 230.2739 |
| 1.465         | 28.57  | 200  | 1.4969          | 137.2427 |
| 1.1617        | 42.86  | 300  | 1.2716          | 76.3242  |
| 1.0019        | 57.14  | 400  | 1.1645          | 71.3756  |
| 0.9052        | 71.43  | 500  | 1.1051          | 69.7866  |
| 0.8334        | 85.71  | 600  | 1.0691          | 68.2657  |
| 0.7838        | 100.0  | 700  | 1.0483          | 67.1686  |
| 0.7539        | 114.29 | 800  | 1.0363          | 66.4195  |
| 0.7377        | 128.57 | 900  | 1.0297          | 66.2001  |
| 0.7325        | 142.86 | 1000 | 1.0277          | 66.0033  |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2