---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- wer
model-index:
- name: whisper-small-Eng-1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: speech_commands
      type: speech_commands
      config: v0.01
      split: test
      args: v0.01
    metrics:
    - name: Wer
      type: wer
      value: 239.6
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-small-Eng-1

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the speech_commands dataset.
It achieves the following results on the evaluation set:
- Loss: 5.0620
- Wer: 239.6

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer   |
|:-------------:|:-----:|:----:|:---------------:|:-----:|
| 7.156         | 0.01  | 5    | 6.9727          | 256.4 |
| 7.5392        | 0.02  | 10   | 5.0620          | 239.6 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3