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

# models

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: 0.0108
- 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.7187        | 1.26  | 500  | 2.7805          | 1.0    |
| 1.3764        | 2.53  | 1000 | 0.2018          | 0.4834 |
| 0.2713        | 3.79  | 1500 | 0.0572          | 0.3337 |
| 0.1924        | 5.05  | 2000 | 0.0486          | 0.3029 |
| 0.1283        | 6.31  | 2500 | 0.0254          | 0.2865 |
| 0.095         | 7.58  | 3000 | 0.0879          | 0.2924 |
| 0.0885        | 8.84  | 3500 | 0.0168          | 0.2702 |
| 0.0662        | 10.1  | 4000 | 0.0196          | 0.2708 |
| 0.0646        | 11.36 | 4500 | 0.0125          | 0.2697 |
| 0.0487        | 12.63 | 5000 | 0.0144          | 0.2691 |
| 0.0539        | 13.89 | 5500 | 0.0172          | 0.2673 |
| 0.0331        | 15.15 | 6000 | 0.0109          | 0.2656 |
| 0.0354        | 16.41 | 6500 | 0.0125          | 0.2656 |
| 0.0194        | 17.68 | 7000 | 0.0115          | 0.2650 |
| 0.0156        | 18.94 | 7500 | 0.0108          | 0.2638 |


### Framework versions

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