---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: openai/whisper-tiny
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: eu
      split: test
      args: eu
    metrics:
    - name: Wer
      type: wer
      value: 33.15849163595123
---

<!-- 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 common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7321
- Wer: 33.1585

## 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: 3.75e-05
- train_batch_size: 256
- eval_batch_size: 128
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0096        | 19.0  | 1000 | 0.5796          | 32.8952 |
| 0.0011        | 38.0  | 2000 | 0.6522          | 32.2694 |
| 0.0005        | 57.01 | 3000 | 0.6949          | 33.1403 |
| 0.0003        | 76.01 | 4000 | 0.7217          | 33.0734 |
| 0.0003        | 96.0  | 5000 | 0.7321          | 33.1585 |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3