---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wavlm-base-plus-ft
  results: []
datasets:
- mazkooleg/0-9up_google_speech_commands_augmented_raw
---

<!-- 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-plus-ft

This model is a fine-tuned version of [microsoft/wavlm-base-plus](https://huggingface.co/microsoft/wavlm-base-plus) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0093
- Accuracy: 0.9973

## 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: 1e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.087         | 1.0   | 8558  | 0.9947   | 0.0216          |
| 0.0439        | 2.0   | 17117 | 0.9964   | 0.0117          |
| 0.0626        | 3.0   | 25675 | 0.9973   | 0.0093          |
| 0.0396        | 4.0   | 34232 | 0.9964   | 0.0097          |
| 0.0417        | 5.0   | 42790 | 0.9964   | 0.0123          |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.11.0
- Datasets 2.10.1
- Tokenizers 0.12.1