pytorch tensorboard wav2vec2 automatic-speech-recognition dataset:common_voice transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-base-1
  results: []
---

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# wav2vec2-base-1

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9254
- Wer: 0.3216

## 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: 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.6597        | 2.2   | 1000  | 0.8904          | 0.5388 |
| 0.4751        | 4.41  | 2000  | 0.7009          | 0.3976 |
| 0.3307        | 6.61  | 3000  | 0.7068          | 0.3672 |
| 0.2574        | 8.81  | 4000  | 0.7320          | 0.3544 |
| 0.2096        | 11.01 | 5000  | 0.7803          | 0.3418 |
| 0.177         | 13.22 | 6000  | 0.7768          | 0.3423 |
| 0.1521        | 15.42 | 7000  | 0.8113          | 0.3375 |
| 0.1338        | 17.62 | 8000  | 0.8153          | 0.3325 |
| 0.1168        | 19.82 | 9000  | 0.8851          | 0.3306 |
| 0.104         | 22.03 | 10000 | 0.8811          | 0.3277 |
| 0.0916        | 24.23 | 11000 | 0.8722          | 0.3254 |
| 0.083         | 26.43 | 12000 | 0.9527          | 0.3265 |
| 0.0766        | 28.63 | 13000 | 0.9254          | 0.3216 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.13.3
- Tokenizers 0.10.3
