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

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: 0.3307
- 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: 8
- eval_batch_size: 2
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3744        | 1.0   | 793  | 0.3307          | 0.8974   |
| 0.3699        | 2.0   | 1586 | 0.3342          | 0.8974   |
| 0.2898        | 3.0   | 2379 | 0.3341          | 0.8974   |
| 0.3126        | 4.0   | 3173 | 0.3363          | 0.8974   |
| 0.3753        | 5.0   | 3966 | 0.3309          | 0.8974   |
| 0.3617        | 6.0   | 4759 | 0.3325          | 0.8974   |
| 0.3453        | 7.0   | 5552 | 0.3315          | 0.8974   |
| 0.3337        | 8.0   | 6346 | 0.3364          | 0.8974   |
| 0.2829        | 9.0   | 7139 | 0.3327          | 0.8974   |
| 0.3189        | 10.0  | 7930 | 0.3321          | 0.8974   |


### Framework versions

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