---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: my_awesome_mind_model
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9805375347544022
---

<!-- 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. -->

# my_awesome_mind_model

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1816
- Accuracy: 0.9805

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.267         | 1.0   | 120  | 2.0147          | 0.9626   |
| 1.309         | 2.0   | 240  | 1.0828          | 0.9731   |
| 0.8739        | 2.99  | 360  | 0.6753          | 0.9759   |
| 0.6183        | 4.0   | 481  | 0.4492          | 0.9781   |
| 0.4868        | 5.0   | 601  | 0.3346          | 0.9771   |
| 0.4124        | 6.0   | 721  | 0.2606          | 0.9787   |
| 0.3495        | 6.99  | 841  | 0.2214          | 0.9808   |
| 0.3073        | 8.0   | 962  | 0.2032          | 0.9790   |
| 0.3264        | 9.0   | 1082 | 0.1862          | 0.9812   |
| 0.3035        | 9.98  | 1200 | 0.1816          | 0.9805   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0