---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: fluent-noisy-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-noisy-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: 0.0129
- Wer: 0.2656

## 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: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.5477        | 1.26  | 500  | 2.9258          | 1.0    |
| 1.6916        | 2.53  | 1000 | 0.4439          | 0.5218 |
| 0.4069        | 3.79  | 1500 | 0.0990          | 0.3524 |
| 0.2584        | 5.05  | 2000 | 0.0812          | 0.3256 |
| 0.1954        | 6.31  | 2500 | 0.0340          | 0.2825 |
| 0.1391        | 7.58  | 3000 | 0.0691          | 0.3046 |
| 0.1378        | 8.84  | 3500 | 0.0334          | 0.2848 |
| 0.1088        | 10.1  | 4000 | 0.0349          | 0.2871 |
| 0.0972        | 11.36 | 4500 | 0.0959          | 0.2761 |
| 0.0883        | 12.63 | 5000 | 0.0229          | 0.2726 |
| 0.0734        | 13.89 | 5500 | 0.0303          | 0.2772 |
| 0.0644        | 15.15 | 6000 | 0.0251          | 0.2755 |
| 0.0536        | 16.41 | 6500 | 0.0139          | 0.2714 |
| 0.0428        | 17.68 | 7000 | 0.0214          | 0.2685 |
| 0.0362        | 18.94 | 7500 | 0.0196          | 0.2667 |
| 0.0377        | 20.2  | 8000 | 0.0257          | 0.2691 |
| 0.0289        | 21.46 | 8500 | 0.0191          | 0.2673 |
| 0.0297        | 22.73 | 9000 | 0.0207          | 0.2667 |
| 0.029         | 23.99 | 9500 | 0.0129          | 0.2656 |


### Framework versions

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