---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: fluent-clean-wav2vec
  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. -->

# fluent-clean-wav2vec

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0100
- Wer: 0.2638

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.7739        | 1.26  | 500   | 2.7988          | 1.0    |
| 1.4369        | 2.53  | 1000  | 0.2079          | 0.5323 |
| 0.2838        | 3.79  | 1500  | 0.0565          | 0.3471 |
| 0.1845        | 5.05  | 2000  | 0.0435          | 0.3209 |
| 0.1383        | 6.31  | 2500  | 0.0284          | 0.3011 |
| 0.1131        | 7.58  | 3000  | 0.4893          | 0.2964 |
| 0.1127        | 8.84  | 3500  | 0.0340          | 0.2702 |
| 0.0942        | 10.1  | 4000  | 0.0155          | 0.2732 |
| 0.0779        | 11.36 | 4500  | 0.0134          | 0.2667 |
| 0.0665        | 12.63 | 5000  | 0.0130          | 0.2732 |
| 0.0619        | 13.89 | 5500  | 0.0163          | 0.2667 |
| 0.0539        | 15.15 | 6000  | 0.0514          | 0.2650 |
| 0.0456        | 16.41 | 6500  | 0.0110          | 0.2662 |
| 0.0405        | 17.68 | 7000  | 0.0105          | 0.2667 |
| 0.0343        | 18.94 | 7500  | 0.0297          | 0.2667 |
| 0.0325        | 20.2  | 8000  | 0.0109          | 0.2656 |
| 0.0241        | 21.46 | 8500  | 0.0109          | 0.2662 |
| 0.0214        | 22.73 | 9000  | 0.0136          | 0.2644 |
| 0.0215        | 23.99 | 9500  | 0.0101          | 0.2638 |
| 0.0215        | 25.25 | 10000 | 0.0101          | 0.2667 |
| 0.0226        | 26.52 | 10500 | 0.0096          | 0.2638 |
| 0.012         | 27.78 | 11000 | 0.0091          | 0.2644 |
| 0.0111        | 29.04 | 11500 | 0.0100          | 0.2638 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2