---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- accuracy
model-index:
- name: audio_classification_example
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: minds14
      type: minds14
      config: en-US
      split: train
      args: en-US
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.07079646017699115
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# audio_classification_example

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6501
- Accuracy: 0.0708

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.6446        | 0.99  | 28   | 2.6533          | 0.0708   |
| 2.6501        | 1.98  | 56   | 2.6360          | 0.0442   |
| 2.6415        | 2.97  | 84   | 2.6452          | 0.0708   |
| 2.6469        | 4.0   | 113  | 2.6508          | 0.0708   |
| 2.6372        | 4.99  | 141  | 2.6463          | 0.0708   |
| 2.6364        | 5.98  | 169  | 2.6467          | 0.0708   |
| 2.6279        | 6.97  | 197  | 2.6497          | 0.0708   |
| 2.6331        | 8.0   | 226  | 2.6510          | 0.0708   |
| 2.6312        | 8.99  | 254  | 2.6504          | 0.0708   |
| 2.6214        | 9.91  | 280  | 2.6501          | 0.0708   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0