---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: wav2vec2-classifier
  results: []
---

<!-- 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. -->

# wav2vec2-classifier

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0684
- Accuracy: 0.4474
- Precision: 0.3646
- Recall: 0.4474
- F1: 0.3683
- Binary: 0.6094

## 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
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Binary |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| No log        | 0.96  | 50   | 4.2611          | 0.0647   | 0.0196    | 0.0647 | 0.0252 | 0.3121 |
| 4.403         | 1.91  | 100  | 3.9746          | 0.0889   | 0.0305    | 0.0889 | 0.0343 | 0.3509 |
| 4.1379        | 2.87  | 150  | 3.7561          | 0.1698   | 0.0733    | 0.1698 | 0.0880 | 0.4135 |
| 3.8988        | 3.83  | 200  | 3.5600          | 0.2372   | 0.1619    | 0.2372 | 0.1527 | 0.4652 |
| 3.6407        | 4.78  | 250  | 3.4072          | 0.3019   | 0.2248    | 0.3019 | 0.2174 | 0.5100 |
| 3.5551        | 5.74  | 300  | 3.2951          | 0.3720   | 0.2851    | 0.3720 | 0.2858 | 0.5555 |
| 3.4319        | 6.7   | 350  | 3.2052          | 0.4070   | 0.3239    | 0.4070 | 0.3214 | 0.5803 |
| 3.3287        | 7.66  | 400  | 3.1429          | 0.4151   | 0.3738    | 0.4151 | 0.3421 | 0.5868 |
| 3.1949        | 8.61  | 450  | 3.0862          | 0.4555   | 0.3707    | 0.4555 | 0.3759 | 0.6178 |
| 3.2056        | 9.57  | 500  | 3.0684          | 0.4474   | 0.3646    | 0.4474 | 0.3683 | 0.6094 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.15.1