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-2
  results: []
---

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# wav2vec2-base-2

This model is a fine-tuned version of [jiobiala24/wav2vec2-base-1](https://huggingface.co/jiobiala24/wav2vec2-base-1) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9415
- Wer: 0.3076

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.4206        | 1.96  | 1000  | 0.6022          | 0.3435 |
| 0.3278        | 3.93  | 2000  | 0.6191          | 0.3344 |
| 0.2604        | 5.89  | 3000  | 0.6170          | 0.3288 |
| 0.2135        | 7.86  | 4000  | 0.6590          | 0.3239 |
| 0.1805        | 9.82  | 5000  | 0.7359          | 0.3289 |
| 0.1582        | 11.79 | 6000  | 0.7450          | 0.3276 |
| 0.1399        | 13.75 | 7000  | 0.7914          | 0.3218 |
| 0.1252        | 15.72 | 8000  | 0.8254          | 0.3185 |
| 0.1095        | 17.68 | 9000  | 0.8524          | 0.3184 |
| 0.1           | 19.65 | 10000 | 0.8340          | 0.3165 |
| 0.0905        | 21.61 | 11000 | 0.8846          | 0.3161 |
| 0.0819        | 23.58 | 12000 | 0.8994          | 0.3142 |
| 0.0763        | 25.54 | 13000 | 0.9018          | 0.3134 |
| 0.0726        | 27.5  | 14000 | 0.9552          | 0.3081 |
| 0.0668        | 29.47 | 15000 | 0.9415          | 0.3076 |


### Framework versions

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