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---
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: 0.2990499031454663
---
<!-- 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/wav2vec2-xls-r-164m-id](https://huggingface.co/evanarlian/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: 0.3510
- Wer: 0.2990
## 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-05
- 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: 0.2
- num_epochs: 50.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.089 | 1.84 | 2000 | 0.3205 | 0.3168 |
| 0.0882 | 3.67 | 4000 | 0.3243 | 0.3203 |
| 0.0868 | 5.51 | 6000 | 0.3272 | 0.3183 |
| 0.0926 | 7.35 | 8000 | 0.3365 | 0.3209 |
| 0.0943 | 9.18 | 10000 | 0.3400 | 0.3221 |
| 0.0979 | 11.02 | 12000 | 0.3269 | 0.3192 |
| 0.09 | 12.86 | 14000 | 0.3384 | 0.3164 |
| 0.0877 | 14.69 | 16000 | 0.3284 | 0.3183 |
| 0.0808 | 16.53 | 18000 | 0.3366 | 0.3189 |
| 0.0835 | 18.37 | 20000 | 0.3306 | 0.3156 |
| 0.08 | 20.2 | 22000 | 0.3384 | 0.3133 |
| 0.0806 | 22.04 | 24000 | 0.3307 | 0.3109 |
| 0.0749 | 23.88 | 26000 | 0.3493 | 0.3118 |
| 0.073 | 25.71 | 28000 | 0.3479 | 0.3088 |
| 0.0754 | 27.55 | 30000 | 0.3482 | 0.3109 |
| 0.0697 | 29.38 | 32000 | 0.3515 | 0.3090 |
| 0.07 | 31.22 | 34000 | 0.3532 | 0.3101 |
| 0.0672 | 33.06 | 36000 | 0.3668 | 0.3086 |
| 0.0713 | 34.89 | 38000 | 0.3560 | 0.3048 |
| 0.0637 | 36.73 | 40000 | 0.3522 | 0.3028 |
| 0.0695 | 38.57 | 42000 | 0.3407 | 0.3014 |
| 0.0657 | 40.4 | 44000 | 0.3456 | 0.3025 |
| 0.0598 | 42.24 | 46000 | 0.3498 | 0.3013 |
| 0.059 | 44.08 | 48000 | 0.3563 | 0.3012 |
| 0.0645 | 45.91 | 50000 | 0.3514 | 0.3002 |
| 0.0595 | 47.75 | 52000 | 0.3545 | 0.3000 |
| 0.064 | 49.59 | 54000 | 0.3510 | 0.2990 |
### Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
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