---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- f1
- precision
- recall
model-index:
- name: my_awesome_mind_model
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: initial_audio
      split: test
      args: initial_audio
    metrics:
    - name: F1
      type: f1
      value: 0.2564102564102564
    - name: Precision
      type: precision
      value: 0.7142857142857143
    - name: Recall
      type: recall
      value: 0.15625
---

<!-- 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: 0.6889
- F1: 0.2564
- Precision: 0.7143
- Recall: 0.1562

## 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 | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
| No log        | 1.0   | 2    | 0.6914          | 0.2162 | 0.8       | 0.125  |
| No log        | 2.0   | 4    | 0.6894          | 0.4815 | 0.5909    | 0.4062 |
| No log        | 3.0   | 6    | 0.6887          | 0.3256 | 0.6364    | 0.2188 |
| No log        | 4.0   | 8    | 0.6881          | 0.3415 | 0.7778    | 0.2188 |
| 0.6907        | 5.0   | 10   | 0.6883          | 0.3415 | 0.7778    | 0.2188 |
| 0.6907        | 6.0   | 12   | 0.6890          | 0.2564 | 0.7143    | 0.1562 |
| 0.6907        | 7.0   | 14   | 0.6894          | 0.2564 | 0.7143    | 0.1562 |
| 0.6907        | 8.0   | 16   | 0.6894          | 0.2105 | 0.6667    | 0.125  |
| 0.6907        | 9.0   | 18   | 0.6890          | 0.2564 | 0.7143    | 0.1562 |
| 0.6851        | 10.0  | 20   | 0.6889          | 0.2564 | 0.7143    | 0.1562 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1
- Datasets 3.0.0
- Tokenizers 0.19.1