---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: openai/whisper-tiny
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fleurs
      type: fleurs
      config: en_us
      split: validation
      args: en_us
    metrics:
    - name: Wer
      type: wer
      value: 19.3465805193222
---

<!-- 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-tiny

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5568
- Wer: 19.3466

## 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_ratio: 0.2
- training_steps: 407
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.1599        | 0.1   | 40   | 1.1427          | 15.2139 |
| 0.4655        | 1.1   | 80   | 0.5613          | 17.5911 |
| 0.2753        | 2.09  | 120  | 0.5241          | 17.2132 |
| 0.2077        | 3.09  | 160  | 0.5242          | 17.2620 |
| 0.1636        | 4.09  | 200  | 0.5290          | 17.6643 |
| 0.1322        | 5.09  | 240  | 0.5351          | 18.2128 |
| 0.123         | 6.08  | 280  | 0.5429          | 18.9077 |
| 0.1074        | 7.08  | 320  | 0.5500          | 19.0540 |
| 0.1007        | 8.08  | 360  | 0.5553          | 19.3100 |
| 0.0876        | 9.08  | 400  | 0.5568          | 19.3466 |


### Framework versions

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