transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice base_model:facebook/wav2vec2-large-xlsr-53 license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: Model_G_2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice
      type: common_voice
      config: id
      split: test
      args: id
    metrics:
    - name: Wer
      type: wer
      value: 0.251258623904531
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Model_G_2

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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3710
- Wer: 0.2513
- Cer: 0.0631

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 3.7484        | 3.23  | 400  | 0.5706          | 0.5698 | 0.1477 |
| 0.3419        | 6.45  | 800  | 0.4120          | 0.3758 | 0.0924 |
| 0.1796        | 9.68  | 1200 | 0.3691          | 0.3295 | 0.0843 |
| 0.125         | 12.9  | 1600 | 0.3821          | 0.3097 | 0.0782 |
| 0.0984        | 16.13 | 2000 | 0.4085          | 0.2947 | 0.0742 |
| 0.0827        | 19.35 | 2400 | 0.3859          | 0.2781 | 0.0711 |
| 0.0666        | 22.58 | 2800 | 0.3813          | 0.2663 | 0.0684 |
| 0.0558        | 25.81 | 3200 | 0.3681          | 0.2545 | 0.0644 |
| 0.0466        | 29.03 | 3600 | 0.3710          | 0.2513 | 0.0631 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 1.18.3
- Tokenizers 0.13.3
