---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-base_music_speech_both_classification
  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-base_music_speech_both_classification

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0586
- Accuracy: 0.9847

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 500
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9458        | 1.0   | 66   | 0.8468          | 0.7405   |
| 0.3785        | 2.0   | 132  | 0.2951          | 0.9771   |
| 0.1762        | 3.0   | 198  | 0.2639          | 0.9313   |
| 0.134         | 4.0   | 264  | 0.1084          | 0.9771   |
| 0.0782        | 5.0   | 330  | 0.0877          | 0.9771   |
| 0.0568        | 6.0   | 396  | 0.0912          | 0.9771   |
| 0.0122        | 7.0   | 462  | 0.4056          | 0.9198   |
| 0.059         | 8.0   | 528  | 0.0586          | 0.9847   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3