---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: my_april11_model
  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: 1.0
---

<!-- 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_april11_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: 0.0029
- Accuracy: 1.0

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6926        | 1.0     | 11   | 0.7243          | 0.2857   |
| 0.6444        | 2.0     | 22   | 0.6651          | 0.5714   |
| 0.5187        | 3.0     | 33   | 0.5439          | 0.7619   |
| 0.4879        | 4.0     | 44   | 0.4134          | 0.8571   |
| 0.3367        | 5.0     | 55   | 0.3302          | 0.8571   |
| 0.2124        | 6.0     | 66   | 0.1248          | 1.0      |
| 0.2257        | 7.0     | 77   | 0.3286          | 0.8571   |
| 0.1128        | 8.0     | 88   | 0.0331          | 1.0      |
| 0.1117        | 9.0     | 99   | 0.0209          | 1.0      |
| 0.0178        | 10.0    | 110  | 0.0142          | 1.0      |
| 0.0149        | 11.0    | 121  | 0.0106          | 1.0      |
| 0.0119        | 12.0    | 132  | 0.0084          | 1.0      |
| 0.01          | 13.0    | 143  | 0.0070          | 1.0      |
| 0.0086        | 14.0    | 154  | 0.0061          | 1.0      |
| 0.0065        | 15.0    | 165  | 0.0053          | 1.0      |
| 0.0065        | 16.0    | 176  | 0.0048          | 1.0      |
| 0.006         | 17.0    | 187  | 0.0044          | 1.0      |
| 0.0055        | 18.0    | 198  | 0.0040          | 1.0      |
| 0.0052        | 19.0    | 209  | 0.0038          | 1.0      |
| 0.0043        | 20.0    | 220  | 0.0035          | 1.0      |
| 0.0045        | 21.0    | 231  | 0.0034          | 1.0      |
| 0.0044        | 22.0    | 242  | 0.0033          | 1.0      |
| 0.0042        | 23.0    | 253  | 0.0031          | 1.0      |
| 0.0041        | 24.0    | 264  | 0.0030          | 1.0      |
| 0.0036        | 25.0    | 275  | 0.0030          | 1.0      |
| 0.0041        | 26.0    | 286  | 0.0029          | 1.0      |
| 0.0039        | 27.0    | 297  | 0.0029          | 1.0      |
| 0.0035        | 27.2857 | 300  | 0.0029          | 1.0      |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0