---
base_model: microsoft/wavlm-base
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wavlm-base_3
  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. -->

# wavlm-base_3

This model is a fine-tuned version of [microsoft/wavlm-base](https://huggingface.co/microsoft/wavlm-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6534
- Accuracy: 0.8974

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 2
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2236        | 1.24  | 100  | 12.8495         | 0.4467   |
| 0.0514        | 2.48  | 200  | 16.3078         | 0.2677   |
| 0.0           | 3.72  | 300  | 17.5651         | 0.2597   |
| 0.3252        | 4.95  | 400  | 15.0382         | 0.1912   |
| 1.0577        | 6.19  | 500  | 0.6534          | 0.8974   |
| 0.6973        | 7.43  | 600  | 0.7352          | 0.1026   |
| 0.6939        | 8.67  | 700  | 0.6210          | 0.8974   |
| 0.6944        | 9.91  | 800  | 0.7129          | 0.1026   |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.0.post302
- Datasets 2.14.5
- Tokenizers 0.13.3