---
tags:
- generated_from_trainer
datasets:
- evanarlian/common_voice_11_0_id_filtered
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-164m-id
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: evanarlian/common_voice_11_0_id_filtered
      type: evanarlian/common_voice_11_0_id_filtered
    metrics:
    - name: Wer
      type: wer
      value: 0.2923162069919749
---

<!-- 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-xls-r-164m-id

This model is a fine-tuned version of [evanarlian/distil-wav2vec2-xls-r-164m-id](https://huggingface.co/evanarlian/distil-wav2vec2-xls-r-164m-id) on the evanarlian/common_voice_11_0_id_filtered dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2865
- Wer: 0.2923

## 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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 80.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.4047        | 4.59  | 5000  | 1.0167          | 0.9138 |
| 0.587         | 9.18  | 10000 | 0.4639          | 0.5615 |
| 0.3782        | 13.77 | 15000 | 0.3375          | 0.4496 |
| 0.2867        | 18.37 | 20000 | 0.2881          | 0.4022 |
| 0.2519        | 22.96 | 25000 | 0.2775          | 0.3700 |
| 0.1941        | 27.55 | 30000 | 0.2701          | 0.3516 |
| 0.1727        | 32.14 | 35000 | 0.2795          | 0.3486 |
| 0.1448        | 36.73 | 40000 | 0.2878          | 0.3364 |
| 0.1251        | 41.32 | 45000 | 0.2649          | 0.3275 |
| 0.113         | 45.91 | 50000 | 0.2862          | 0.3168 |
| 0.0994        | 50.51 | 55000 | 0.2798          | 0.3091 |
| 0.0938        | 55.1  | 60000 | 0.2864          | 0.3070 |
| 0.0853        | 59.69 | 65000 | 0.2860          | 0.3069 |
| 0.0724        | 64.28 | 70000 | 0.2994          | 0.3003 |
| 0.0723        | 68.87 | 75000 | 0.2951          | 0.2983 |
| 0.0666        | 73.46 | 80000 | 0.2886          | 0.2941 |
| 0.0659        | 78.05 | 85000 | 0.2865          | 0.2923 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2