---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: result
  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: 0.9690721649484536
---

<!-- 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. -->

# result

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: 0.9485
- Accuracy: 0.9691

## 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: 35

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.9231  | 3    | 1.7283          | 0.9072   |
| No log        | 1.8462  | 6    | 1.7069          | 0.9072   |
| No log        | 2.7692  | 9    | 1.6799          | 0.9485   |
| 1.7783        | 4.0     | 13   | 1.6130          | 0.9278   |
| 1.7783        | 4.9231  | 16   | 1.5587          | 0.9485   |
| 1.7783        | 5.8462  | 19   | 1.5084          | 0.9691   |
| 1.6476        | 6.7692  | 22   | 1.4736          | 0.9485   |
| 1.6476        | 8.0     | 26   | 1.4109          | 0.9691   |
| 1.6476        | 8.9231  | 29   | 1.3672          | 0.9485   |
| 1.4942        | 9.8462  | 32   | 1.3308          | 0.9588   |
| 1.4942        | 10.7692 | 35   | 1.2972          | 0.9588   |
| 1.4942        | 12.0    | 39   | 1.2477          | 0.9588   |
| 1.3605        | 12.9231 | 42   | 1.2180          | 0.9588   |
| 1.3605        | 13.8462 | 45   | 1.1982          | 0.9485   |
| 1.3605        | 14.7692 | 48   | 1.1668          | 0.9691   |
| 1.2591        | 16.0    | 52   | 1.1356          | 0.9691   |
| 1.2591        | 16.9231 | 55   | 1.1097          | 0.9691   |
| 1.2591        | 17.8462 | 58   | 1.0918          | 0.9691   |
| 1.1784        | 18.7692 | 61   | 1.0711          | 0.9691   |
| 1.1784        | 20.0    | 65   | 1.0505          | 0.9691   |
| 1.1784        | 20.9231 | 68   | 1.0345          | 0.9691   |
| 1.1179        | 21.8462 | 71   | 1.0211          | 0.9691   |
| 1.1179        | 22.7692 | 74   | 1.0102          | 0.9691   |
| 1.1179        | 24.0    | 78   | 0.9949          | 0.9691   |
| 1.0669        | 24.9231 | 81   | 0.9835          | 0.9794   |
| 1.0669        | 25.8462 | 84   | 0.9774          | 0.9691   |
| 1.0669        | 26.7692 | 87   | 0.9736          | 0.9588   |
| 1.0398        | 28.0    | 91   | 0.9644          | 0.9691   |
| 1.0398        | 28.9231 | 94   | 0.9588          | 0.9794   |
| 1.0398        | 29.8462 | 97   | 0.9533          | 0.9691   |
| 1.0303        | 30.7692 | 100  | 0.9496          | 0.9691   |
| 1.0303        | 32.0    | 104  | 0.9485          | 0.9691   |
| 1.0303        | 32.3077 | 105  | 0.9485          | 0.9691   |


### Framework versions

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