---
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: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.2793103448275862
---

<!-- 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: 2.3078
- Accuracy: 0.2793

## 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.73  | 2    | 2.6832          | 0.1241   |
| No log        | 1.82  | 5    | 2.6800          | 0.1103   |
| No log        | 2.91  | 8    | 2.6726          | 0.1207   |
| 2.6498        | 4.0   | 11   | 2.6580          | 0.1483   |
| 2.6498        | 4.73  | 13   | 2.6454          | 0.1379   |
| 2.6498        | 5.82  | 16   | 2.6245          | 0.1379   |
| 2.6498        | 6.91  | 19   | 2.6038          | 0.1414   |
| 2.6057        | 8.0   | 22   | 2.5839          | 0.1552   |
| 2.6057        | 8.73  | 24   | 2.5656          | 0.1655   |
| 2.6057        | 9.82  | 27   | 2.5378          | 0.1552   |
| 2.524         | 10.91 | 30   | 2.5192          | 0.1862   |
| 2.524         | 12.0  | 33   | 2.4996          | 0.1931   |
| 2.524         | 12.73 | 35   | 2.4900          | 0.2069   |
| 2.524         | 13.82 | 38   | 2.4663          | 0.2138   |
| 2.4304        | 14.91 | 41   | 2.4498          | 0.2207   |
| 2.4304        | 16.0  | 44   | 2.4309          | 0.2138   |
| 2.4304        | 16.73 | 46   | 2.4291          | 0.2310   |
| 2.4304        | 17.82 | 49   | 2.4106          | 0.2517   |
| 2.3519        | 18.91 | 52   | 2.3944          | 0.2310   |
| 2.3519        | 20.0  | 55   | 2.3949          | 0.2414   |
| 2.3519        | 20.73 | 57   | 2.3807          | 0.2414   |
| 2.2774        | 21.82 | 60   | 2.3661          | 0.2379   |
| 2.2774        | 22.91 | 63   | 2.3600          | 0.2345   |
| 2.2774        | 24.0  | 66   | 2.3572          | 0.2483   |
| 2.2774        | 24.73 | 68   | 2.3430          | 0.2345   |
| 2.2402        | 25.82 | 71   | 2.3369          | 0.2586   |
| 2.2402        | 26.91 | 74   | 2.3365          | 0.2586   |
| 2.2402        | 28.0  | 77   | 2.3301          | 0.2621   |
| 2.2402        | 28.73 | 79   | 2.3274          | 0.2724   |
| 2.1901        | 29.82 | 82   | 2.3266          | 0.2759   |
| 2.1901        | 30.91 | 85   | 2.3207          | 0.2655   |
| 2.1901        | 32.0  | 88   | 2.3115          | 0.2724   |
| 2.148         | 32.73 | 90   | 2.3084          | 0.2724   |
| 2.148         | 33.82 | 93   | 2.3082          | 0.2724   |
| 2.148         | 34.91 | 96   | 2.3094          | 0.2828   |
| 2.148         | 36.0  | 99   | 2.3080          | 0.2793   |
| 2.1303        | 36.36 | 100  | 2.3078          | 0.2793   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0