---
language:
- sat
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- sat
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-sat-final
  results:
  - task: 
      name: Automatic Speech Recognition 
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 8
      type: mozilla-foundation/common_voice_8_0
      args: sat
    metrics:
       - name: Test WER
         type: wer
         value: 0.3493975903614458
       - name: Test CER
         type: cer
         value: 0.13773314203730272
---

<!-- 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-large-xls-r-300m-sat-final

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8012
- Wer: 0.3815

## 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: 0.0004
- 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: 170
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 10.6317       | 33.29  | 100  | 2.8629          | 1.0    |
| 2.047         | 66.57  | 200  | 0.9516          | 0.5703 |
| 0.4475        | 99.86  | 300  | 0.8539          | 0.3896 |
| 0.0716        | 133.29 | 400  | 0.8277          | 0.3454 |
| 0.047         | 166.57 | 500  | 0.7597          | 0.3655 |
| 0.0249        | 199.86 | 600  | 0.8012          | 0.3815 |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0