---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: result1
  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: 0.979381443298969
---

<!-- 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. -->

# result1

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: 1.1566
- Accuracy: 0.9794

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.9231 | 3    | 1.3671          | 0.9588   |
| No log        | 1.8462 | 6    | 1.3125          | 0.9897   |
| No log        | 2.7692 | 9    | 1.2705          | 0.9691   |
| 1.372         | 4.0    | 13   | 1.2335          | 0.9794   |
| 1.372         | 4.9231 | 16   | 1.2130          | 0.9897   |
| 1.372         | 5.8462 | 19   | 1.1962          | 0.9794   |
| 1.2696        | 6.7692 | 22   | 1.1803          | 0.9794   |
| 1.2696        | 8.0    | 26   | 1.1640          | 0.9794   |
| 1.2696        | 8.9231 | 29   | 1.1574          | 0.9794   |
| 1.208         | 9.2308 | 30   | 1.1566          | 0.9794   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.1.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1