pytorch 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-cv
  results: []
---

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# wav2vec2-base-cv

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: 1.1562
- Wer: 0.3804

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.563         | 3.18  | 500  | 2.9826          | 1.0    |
| 2.0012        | 6.37  | 1000 | 0.9528          | 0.5354 |
| 0.4841        | 9.55  | 1500 | 0.8838          | 0.4325 |
| 0.2748        | 12.74 | 2000 | 0.9437          | 0.4130 |
| 0.1881        | 15.92 | 2500 | 0.9603          | 0.4005 |
| 0.1426        | 19.11 | 3000 | 1.0605          | 0.3955 |
| 0.1134        | 22.29 | 3500 | 1.0733          | 0.3897 |
| 0.0963        | 25.48 | 4000 | 1.1387          | 0.3835 |
| 0.0829        | 28.66 | 4500 | 1.1562          | 0.3804 |


### Framework versions

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