---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: my_forgetful_mind_model2
  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: 0.9891304347826086
---

<!-- 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_forgetful_mind_model2

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: 0.0529
- Accuracy: 0.9891

## 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: 11

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6716        | 0.9655  | 14   | 0.6144          | 0.6630   |
| 0.5768        | 2.0     | 29   | 0.2991          | 0.9304   |
| 0.2108        | 2.9655  | 43   | 0.2372          | 0.9130   |
| 0.2452        | 4.0     | 58   | 0.1582          | 0.9565   |
| 0.1006        | 4.9655  | 72   | 0.0831          | 0.9848   |
| 0.0773        | 6.0     | 87   | 0.1206          | 0.9696   |
| 0.0477        | 6.9655  | 101  | 0.0585          | 0.9913   |
| 0.0431        | 8.0     | 116  | 0.0643          | 0.9870   |
| 0.0303        | 8.9655  | 130  | 0.0526          | 0.9891   |
| 0.0336        | 10.0    | 145  | 0.0523          | 0.9891   |
| 0.0285        | 10.6207 | 154  | 0.0529          | 0.9891   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1