---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-demo-colab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: sah
      split: test
      args: sah
    metrics:
    - name: Wer
      type: wer
      value: 0.5698038864511508
---

<!-- 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-xlsr-53-demo-colab

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8836
- Wer: 0.5698

## 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: 0.0003
- 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1354        | 14.04 | 400  | 0.8703          | 0.6377 |
| 0.1297        | 28.07 | 800  | 0.8601          | 0.6317 |
| 0.0937        | 42.11 | 1200 | 0.9103          | 0.6320 |
| 0.0751        | 56.14 | 1600 | 0.8848          | 0.6044 |
| 0.0582        | 70.18 | 2000 | 0.8630          | 0.5770 |
| 0.0492        | 84.21 | 2400 | 0.8889          | 0.5786 |
| 0.0402        | 98.25 | 2800 | 0.8836          | 0.5698 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1