---
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: cmn_hans_cn
      split: test
      args: cmn_hans_cn
    metrics:
    - name: Wer
      type: wer
      value: 16.05478120919498
---

<!-- 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: 0.3537
- Wer: 16.0548

## 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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0013        | 19.01 | 1000 | 0.2910          | 14.9282 |
| 0.0005        | 39.0  | 2000 | 0.3185          | 15.6327 |
| 0.0002        | 58.01 | 3000 | 0.3369          | 15.6965 |
| 0.0002        | 78.0  | 4000 | 0.3480          | 16.0669 |
| 0.0001        | 98.0  | 5000 | 0.3537          | 16.0548 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2