---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-librispeech32
  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. -->

# wav2vec2-base-librispeech32

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: 0.3137
- Wer: 0.1101

## 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: 32
- eval_batch_size: 32
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.6899        | 2.07  | 500  | 2.7071          | 0.9991 |
| 0.5624        | 4.13  | 1000 | 0.4322          | 0.2304 |
| 0.1855        | 6.2   | 1500 | 0.4234          | 0.2023 |
| 0.1224        | 8.26  | 2000 | 0.4044          | 0.1852 |
| 0.0928        | 10.33 | 2500 | 0.4644          | 0.2213 |
| 0.0766        | 12.4  | 3000 | 0.3669          | 0.1459 |
| 0.0655        | 14.46 | 3500 | 0.3215          | 0.1414 |
| 0.0544        | 16.53 | 4000 | 0.3524          | 0.1292 |
| 0.0475        | 18.6  | 4500 | 0.4299          | 0.1818 |
| 0.0405        | 20.66 | 5000 | 0.3026          | 0.1226 |
| 0.0361        | 22.73 | 5500 | 0.3132          | 0.1206 |
| 0.0329        | 24.79 | 6000 | 0.3409          | 0.1086 |
| 0.03          | 26.86 | 6500 | 0.3183          | 0.1099 |
| 0.0276        | 28.93 | 7000 | 0.3137          | 0.1101 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3