---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wavLM-base-UTCN
  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-UTCN

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: 0.0234
- Accuracy: 0.9962

## 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: 16
- eval_batch_size: 16
- seed: 42
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0603        | 1.0   | 435  | 0.0307          | 0.9928   |
| 0.009         | 2.0   | 870  | 0.0201          | 0.9962   |
| 0.0109        | 3.0   | 1305 | 0.0176          | 0.9972   |
| 0.001         | 4.0   | 1740 | 0.0246          | 0.9950   |
| 0.0013        | 5.0   | 2175 | 0.0234          | 0.9962   |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3


arxiv.org/abs/2408.07414