---
license: mit
base_model: distil-whisper/distil-small.en
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: distil-small.en-speech-commands
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: speech_commands
      type: speech_commands
      config: v0.02
      split: None
      args: v0.02
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8066546762589928
---

<!-- 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. -->

# distil-small.en-speech-commands

This model is a fine-tuned version of [distil-whisper/distil-small.en](https://huggingface.co/distil-whisper/distil-small.en) on the speech_commands dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9307
- Accuracy: 0.8067

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1861        | 1.0   | 618  | 0.7743          | 0.8022   |
| 0.1135        | 2.0   | 1236 | 0.9853          | 0.8049   |
| 0.078         | 3.0   | 1854 | 0.9307          | 0.8067   |
| 0.038         | 4.0   | 2472 | 0.9989          | 0.8049   |
| 0.0375        | 5.0   | 3090 | 1.0738          | 0.8035   |
| 0.0462        | 6.0   | 3708 | 1.1601          | 0.8067   |
| 0.018         | 7.0   | 4326 | 1.5369          | 0.8067   |
| 0.0008        | 8.0   | 4944 | 1.2515          | 0.8067   |
| 0.0016        | 9.0   | 5562 | 1.3494          | 0.8058   |
| 0.0002        | 10.0  | 6180 | 1.5117          | 0.8053   |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1