---
language:
- eo
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_13_0
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-common_voice_13_0-eo-10_1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - EO
      type: common_voice_13_0
      config: eo
      split: validation
      args: 'Config: eo, Training split: train, Eval split: validation'
    metrics:
    - name: Wer
      type: wer
      value: 0.05342994850125446
---

<!-- 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-10_1

This model is a fine-tuned version of [xekri/wav2vec2-common_voice_13_0-eo-10](https://huggingface.co/xekri/wav2vec2-common_voice_13_0-eo-10) on the MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - EO dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0391
- Cer: 0.0098
- Wer: 0.0534

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer    | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 0.1142        | 0.22  | 1000  | 0.0483          | 0.0126 | 0.0707 |
| 0.1049        | 0.44  | 2000  | 0.0474          | 0.0123 | 0.0675 |
| 0.0982        | 0.67  | 3000  | 0.0471          | 0.0120 | 0.0664 |
| 0.092         | 0.89  | 4000  | 0.0459          | 0.0117 | 0.0640 |
| 0.0847        | 1.11  | 5000  | 0.0459          | 0.0115 | 0.0631 |
| 0.0837        | 1.33  | 6000  | 0.0453          | 0.0113 | 0.0624 |
| 0.0803        | 1.56  | 7000  | 0.0443          | 0.0109 | 0.0598 |
| 0.0826        | 1.78  | 8000  | 0.0441          | 0.0110 | 0.0604 |
| 0.0809        | 2.0   | 9000  | 0.0437          | 0.0110 | 0.0605 |
| 0.0728        | 2.22  | 10000 | 0.0451          | 0.0109 | 0.0597 |
| 0.0707        | 2.45  | 11000 | 0.0444          | 0.0108 | 0.0591 |
| 0.0698        | 2.67  | 12000 | 0.0442          | 0.0105 | 0.0576 |
| 0.0981        | 2.89  | 13000 | 0.0411          | 0.0104 | 0.0572 |
| 0.0928        | 3.11  | 14000 | 0.0413          | 0.0102 | 0.0561 |
| 0.0927        | 3.34  | 15000 | 0.0410          | 0.0102 | 0.0565 |
| 0.0886        | 3.56  | 16000 | 0.0402          | 0.0102 | 0.0558 |
| 0.091         | 3.78  | 17000 | 0.0400          | 0.0101 | 0.0553 |
| 0.0888        | 4.0   | 18000 | 0.0398          | 0.0100 | 0.0546 |
| 0.0885        | 4.23  | 19000 | 0.0395          | 0.0099 | 0.0542 |
| 0.0869        | 4.45  | 20000 | 0.0394          | 0.0099 | 0.0540 |
| 0.0844        | 4.67  | 21000 | 0.0393          | 0.0098 | 0.0539 |
| 0.0882        | 4.89  | 22000 | 0.0391          | 0.0098 | 0.0537 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3