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whisper-base.en-speech-commands

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whisper-base.en-speech-commands
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---
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: whisper-base.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: 0.8053057553956835
---

<!-- 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-base.en-speech-commands

This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the speech_commands dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1288
- Accuracy: 0.8053

## 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: 96
- eval_batch_size: 96
- 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2727        | 1.0   | 412  | 0.9931          | 0.8031   |
| 0.1816        | 2.0   | 824  | 1.1288          | 0.8053   |
| 0.1323        | 3.0   | 1236 | 1.0521          | 0.8008   |
| 0.0551        | 4.0   | 1648 | 1.0061          | 0.7999   |
| 0.0653        | 5.0   | 2060 | 0.9538          | 0.8017   |
| 0.0489        | 6.0   | 2472 | 1.0026          | 0.8017   |
| 0.0326        | 7.0   | 2884 | 1.0090          | 0.8031   |


### Framework versions

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