---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-common_voice_13_0-eo-3
  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-common_voice_13_0-eo-3

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2191
- Cer: 0.0208
- Wer: 0.0686

## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Cer    | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:------:|:---------------:|:------:|
| 2.6416        | 2.13  | 1000  | 0.1541 | 0.8599          | 0.6449 |
| 0.2633        | 4.27  | 2000  | 0.0335 | 0.1897          | 0.1431 |
| 0.1739        | 6.4   | 3000  | 0.0289 | 0.1732          | 0.1145 |
| 0.1378        | 8.53  | 4000  | 0.0276 | 0.1729          | 0.1066 |
| 0.1172        | 10.67 | 5000  | 0.0268 | 0.1773          | 0.1019 |
| 0.1049        | 12.8  | 6000  | 0.0255 | 0.1701          | 0.0937 |
| 0.0951        | 14.93 | 7000  | 0.0253 | 0.1718          | 0.0933 |
| 0.0851        | 17.07 | 8000  | 0.0239 | 0.1787          | 0.0834 |
| 0.0809        | 19.2  | 9000  | 0.0235 | 0.1802          | 0.0835 |
| 0.0756        | 21.33 | 10000 | 0.0239 | 0.1784          | 0.0855 |
| 0.0708        | 23.47 | 11000 | 0.0235 | 0.1748          | 0.0824 |
| 0.0657        | 25.6  | 12000 | 0.0228 | 0.1830          | 0.0796 |
| 0.0605        | 27.73 | 13000 | 0.0230 | 0.1896          | 0.0798 |
| 0.0583        | 29.87 | 14000 | 0.0224 | 0.1889          | 0.0778 |
| 0.0608        | 32.0  | 15000 | 0.0223 | 0.1849          | 0.0757 |
| 0.0556        | 34.13 | 16000 | 0.0223 | 0.1872          | 0.0767 |
| 0.0534        | 36.27 | 17000 | 0.0221 | 0.1893          | 0.0751 |
| 0.0523        | 38.4  | 18000 | 0.0218 | 0.1925          | 0.0729 |
| 0.0494        | 40.53 | 19000 | 0.0221 | 0.1957          | 0.0745 |
| 0.0475        | 42.67 | 20000 | 0.0217 | 0.1961          | 0.0740 |
| 0.048         | 44.8  | 21000 | 0.0214 | 0.1957          | 0.0714 |
| 0.0459        | 46.93 | 22000 | 0.0215 | 0.1968          | 0.0717 |
| 0.0435        | 49.07 | 23000 | 0.0217 | 0.2008          | 0.0717 |
| 0.0428        | 51.2  | 24000 | 0.0212 | 0.1991          | 0.0696 |
| 0.0418        | 53.33 | 25000 | 0.0215 | 0.2034          | 0.0714 |
| 0.0404        | 55.47 | 26000 | 0.0210 | 0.2014          | 0.0684 |
| 0.0394        | 57.6  | 27000 | 0.0210 | 0.2050          | 0.0681 |
| 0.0399        | 59.73 | 28000 | 0.0211 | 0.2039          | 0.0700 |
| 0.0389        | 61.87 | 29000 | 0.0214 | 0.2091          | 0.0694 |
| 0.038         | 64.0  | 30000 | 0.0210 | 0.2100          | 0.0702 |
| 0.0361        | 66.13 | 31000 | 0.0215 | 0.2119          | 0.0703 |
| 0.0359        | 68.27 | 32000 | 0.0213 | 0.2108          | 0.0714 |
| 0.0354        | 70.4  | 33000 | 0.0211 | 0.2120          | 0.0699 |
| 0.0364        | 72.53 | 34000 | 0.0211 | 0.2128          | 0.0688 |
| 0.0361        | 74.67 | 35000 | 0.0212 | 0.2134          | 0.0694 |
| 0.0332        | 76.8  | 36000 | 0.0210 | 0.2176          | 0.0698 |
| 0.0341        | 78.93 | 37000 | 0.0208 | 0.2170          | 0.0688 |
| 0.032         | 81.07 | 38000 | 0.0209 | 0.2157          | 0.0686 |
| 0.0318        | 83.33 | 39000 | 0.0209 | 0.2166          | 0.0685 |
| 0.0325        | 85.47 | 40000 | 0.2172 | 0.0209          | 0.0687 |
| 0.0316        | 87.6  | 41000 | 0.2181 | 0.0208          | 0.0678 |
| 0.0302        | 89.73 | 42000 | 0.2171 | 0.0208          | 0.0679 |
| 0.0318        | 91.87 | 43000 | 0.2179 | 0.0211          | 0.0702 |
| 0.0314        | 94.0  | 44000 | 0.2186 | 0.0208          | 0.0690 |
| 0.0309        | 96.13 | 45000 | 0.2193 | 0.0210          | 0.0696 |
| 0.031         | 98.27 | 46000 | 0.2191 | 0.0208          | 0.0686 |


### Framework versions

- Transformers 4.29.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3