---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-libri
  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. -->

# w2v2-libri

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7315
- Wer: 0.5574

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-07
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 7.1828        | 50.0  | 200  | 3.0563          | 1.0    |
| 2.8849        | 100.0 | 400  | 2.9023          | 1.0    |
| 1.5108        | 150.0 | 600  | 1.1468          | 0.6667 |
| 0.1372        | 200.0 | 800  | 1.3749          | 0.6279 |
| 0.0816        | 250.0 | 1000 | 1.3985          | 0.6224 |
| 0.0746        | 300.0 | 1200 | 1.5285          | 0.6141 |
| 0.0556        | 350.0 | 1400 | 1.5496          | 0.5920 |
| 0.0644        | 400.0 | 1600 | 1.6263          | 0.5947 |
| 0.0546        | 450.0 | 1800 | 1.6803          | 0.5906 |
| 0.0491        | 500.0 | 2000 | 1.6155          | 0.5837 |
| 0.0518        | 550.0 | 2200 | 1.6784          | 0.5698 |
| 0.0314        | 600.0 | 2400 | 1.6050          | 0.5602 |
| 0.0048        | 650.0 | 2600 | 1.7703          | 0.5546 |
| 0.0042        | 700.0 | 2800 | 1.7135          | 0.5615 |
| 0.0025        | 750.0 | 3000 | 1.7315          | 0.5574 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 1.18.3
- Tokenizers 0.13.2