---
library_name: transformers
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-v1
  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. -->

# whisper-base.en-speech-commands-v1

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: 1.1638
- 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: 96
- eval_batch_size: 96
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 384
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3306        | 1.0   | 103  | 1.1388          | 0.8022   |
| 0.1314        | 2.0   | 206  | 1.1511          | 0.8022   |
| 0.0672        | 3.0   | 309  | 1.1448          | 0.8062   |
| 0.048         | 4.0   | 412  | 1.1638          | 0.8067   |
| 0.034         | 5.0   | 515  | 1.1655          | 0.8058   |


### Framework versions

- Transformers 4.51.2
- Pytorch 2.6.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1