---
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
  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: 0.06566915357190017
---

<!-- 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

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - EO dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0454
- Cer: 0.0118
- Wer: 0.0657

## 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  | Cer    | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:------:|:---------------:|:------:|
| 2.9894        | 0.22  | 1000  | 1.0    | 2.9257          | 1.0    |
| 0.7104        | 0.44  | 2000  | 0.0457 | 0.2129          | 0.2538 |
| 0.2853        | 0.67  | 3000  | 0.0274 | 0.1109          | 0.1583 |
| 0.2327        | 0.89  | 4000  | 0.0231 | 0.0909          | 0.1320 |
| 0.1917        | 1.11  | 5000  | 0.0206 | 0.0775          | 0.1188 |
| 0.1803        | 1.33  | 6000  | 0.0184 | 0.0698          | 0.1055 |
| 0.1661        | 1.56  | 7000  | 0.0169 | 0.0645          | 0.0961 |
| 0.1635        | 1.78  | 8000  | 0.0170 | 0.0639          | 0.0964 |
| 0.1555        | 2.0   | 9000  | 0.0156 | 0.0592          | 0.0881 |
| 0.1386        | 2.22  | 10000 | 0.0147 | 0.0559          | 0.0821 |
| 0.1338        | 2.45  | 11000 | 0.0146 | 0.0548          | 0.0831 |
| 0.1307        | 2.67  | 12000 | 0.0137 | 0.0529          | 0.0759 |
| 0.1297        | 2.89  | 13000 | 0.0134 | 0.0504          | 0.0745 |
| 0.1201        | 3.11  | 14000 | 0.0131 | 0.0499          | 0.0734 |
| 0.1152        | 3.34  | 15000 | 0.0128 | 0.0484          | 0.0712 |
| 0.1144        | 3.56  | 16000 | 0.0125 | 0.0477          | 0.0695 |
| 0.1179        | 3.78  | 17000 | 0.0122 | 0.0468          | 0.0679 |
| 0.1112        | 4.0   | 18000 | 0.0121 | 0.0468          | 0.0676 |
| 0.1141        | 4.23  | 19000 | 0.0121 | 0.0462          | 0.0668 |
| 0.1085        | 4.45  | 20000 | 0.0119 | 0.0458          | 0.0664 |
| 0.105         | 4.67  | 21000 | 0.0119 | 0.0456          | 0.0660 |
| 0.1072        | 4.89  | 22000 | 0.0119 | 0.0454          | 0.0658 |


### Framework versions

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