---
language:
- en
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- speech_command_v0_02
metrics:
- wer
model-index:
- name: Whisper Small command - fatipd
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: speech command v02
      type: speech_command_v0_02
      config: null
      split: None
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.3861003861003861
---

<!-- 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 command - fatipd

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the speech command v02 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0021
- Wer: 0.3861

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 3000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0095        | 0.2   | 250  | 0.0042          | 0.7239 |
| 0.0068        | 0.4   | 500  | 0.0051          | 1.0135 |
| 0.0045        | 0.6   | 750  | 0.0021          | 0.3861 |
| 0.0056        | 0.8   | 1000 | 0.0018          | 1.5927 |
| 0.0021        | 1.0   | 1250 | 0.0023          | 8.8803 |
| 0.0081        | 1.2   | 1500 | 0.0033          | 2.0270 |
| 0.0056        | 1.4   | 1750 | 0.0023          | 6.1293 |
| 0.0028        | 1.6   | 2000 | 0.0017          | 0.8687 |
| 0.0064        | 1.81  | 2250 | 0.0011          | 0.8687 |
| 0.0005        | 2.01  | 2500 | 0.0014          | 2.0270 |
| 0.0015        | 2.21  | 2750 | 0.0013          | 1.4961 |
| 0.0012        | 2.41  | 3000 | 0.0014          | 1.8822 |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3