---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: wav2vec2-base-960h-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. -->

# wav2vec2-base-960h-speech-commands

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on the speech_commands dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1612
- 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: 48
- eval_batch_size: 48
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.745         | 1.0   | 824   | 1.9237          | 0.7648   |
| 0.5664        | 2.0   | 1648  | 1.1424          | 0.7878   |
| 0.4337        | 3.0   | 2472  | 1.1234          | 0.8013   |
| 0.3346        | 4.0   | 3296  | 1.1040          | 0.8035   |
| 0.2683        | 5.0   | 4120  | 1.3128          | 0.7905   |
| 0.3498        | 6.0   | 4944  | 1.2172          | 0.7972   |
| 0.2556        | 7.0   | 5768  | 1.1906          | 0.7986   |
| 0.226         | 8.0   | 6592  | 1.1081          | 0.8044   |
| 0.2317        | 9.0   | 7416  | 1.1068          | 0.8049   |
| 0.1144        | 10.0  | 8240  | 1.1612          | 0.8067   |
| 0.2143        | 11.0  | 9064  | 1.1577          | 0.8031   |
| 0.1668        | 12.0  | 9888  | 1.1343          | 0.8058   |
| 0.2504        | 13.0  | 10712 | 1.0583          | 0.8067   |
| 0.218         | 14.0  | 11536 | 1.0677          | 0.8026   |
| 0.1025        | 15.0  | 12360 | 1.0690          | 0.8053   |


### Framework versions

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