---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: whisper_small_tw12
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: tw
      split: train+test
      args: tw
    metrics:
    - name: Wer
      type: wer
      value: 1.103734439834025
---

<!-- 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. -->

# whisper_small_tw12

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3399
- Wer: 1.1037

## 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: 6.25e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.0649        | 6.25  | 100  | 3.2733          | 1.5726 |
| 0.9932        | 12.5  | 200  | 2.9873          | 1.9378 |
| 0.0521        | 18.75 | 300  | 3.0893          | 1.1203 |
| 0.0045        | 25.0  | 400  | 3.2862          | 1.1245 |
| 0.0025        | 31.25 | 500  | 3.3399          | 1.1037 |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0