---
library_name: transformers
license: apache-2.0
base_model: anton-l/wav2vec2-base-ft-keyword-spotting
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- accuracy
model-index:
- name: wav2vec2-minds14-audio-classification-all
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: minds14
      type: minds14
      config: all
      split: train
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.09730722154222766
---

<!-- 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-minds14-audio-classification-all

This model is a fine-tuned version of [anton-l/wav2vec2-base-ft-keyword-spotting](https://huggingface.co/anton-l/wav2vec2-base-ft-keyword-spotting) on the minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6367
- Accuracy: 0.0973

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.6374        | 0.9951 | 51   | 2.6375          | 0.0894   |
| 2.6347        | 1.9902 | 102  | 2.6334          | 0.0900   |
| 2.6352        | 2.9854 | 153  | 2.6323          | 0.0930   |
| 2.6282        | 4.0    | 205  | 2.6280          | 0.0924   |
| 2.6224        | 4.9951 | 256  | 2.6398          | 0.0894   |
| 2.6122        | 5.9902 | 307  | 2.6306          | 0.0912   |
| 2.6225        | 6.9854 | 358  | 2.6325          | 0.0906   |
| 2.6196        | 8.0    | 410  | 2.6358          | 0.0961   |
| 2.6154        | 8.9951 | 461  | 2.6357          | 0.0924   |
| 2.6028        | 9.9512 | 510  | 2.6367          | 0.0973   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1