---
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: 0.9848965131456274
---

<!-- 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. -->

# 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: 0.0374
- Wer: 0.9849
- Cer: 0.7098

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 3.6149        | 1.07  | 400   | 0.4672          | 1.0114 | 0.7588 |
| 0.4341        | 2.15  | 800   | 0.2008          | 0.9972 | 0.7369 |
| 0.2665        | 3.22  | 1200  | 0.1283          | 0.9986 | 0.7180 |
| 0.2114        | 4.3   | 1600  | 0.1016          | 0.9995 | 0.7135 |
| 0.1768        | 5.37  | 2000  | 0.0774          | 0.9950 | 0.7208 |
| 0.1531        | 6.44  | 2400  | 0.0682          | 0.9933 | 0.7137 |
| 0.1352        | 7.52  | 2800  | 0.0690          | 0.9883 | 0.7022 |
| 0.1252        | 8.59  | 3200  | 0.0656          | 0.9925 | 0.7091 |
| 0.1144        | 9.66  | 3600  | 0.0521          | 0.9888 | 0.7124 |
| 0.0986        | 10.74 | 4000  | 0.0527          | 0.9915 | 0.7067 |
| 0.0875        | 11.81 | 4400  | 0.0531          | 0.9902 | 0.7057 |
| 0.0883        | 12.89 | 4800  | 0.0488          | 0.9888 | 0.7136 |
| 0.0812        | 13.96 | 5200  | 0.0461          | 0.9884 | 0.7122 |
| 0.0721        | 15.03 | 5600  | 0.0474          | 0.9884 | 0.7128 |
| 0.0681        | 16.11 | 6000  | 0.0469          | 0.9869 | 0.7243 |
| 0.0671        | 17.18 | 6400  | 0.0450          | 0.9878 | 0.7086 |
| 0.0613        | 18.26 | 6800  | 0.0492          | 0.9852 | 0.7171 |
| 0.0573        | 19.33 | 7200  | 0.0435          | 0.9852 | 0.7209 |
| 0.0531        | 20.4  | 7600  | 0.0389          | 0.9908 | 0.7071 |
| 0.0493        | 21.48 | 8000  | 0.0423          | 0.9871 | 0.7166 |
| 0.0477        | 22.55 | 8400  | 0.0416          | 0.9843 | 0.7127 |
| 0.0441        | 23.62 | 8800  | 0.0372          | 0.9864 | 0.7075 |
| 0.0412        | 24.7  | 9200  | 0.0408          | 0.9857 | 0.7118 |
| 0.0392        | 25.77 | 9600  | 0.0407          | 0.9851 | 0.7152 |
| 0.0359        | 26.85 | 10000 | 0.0383          | 0.9861 | 0.7086 |
| 0.0347        | 27.92 | 10400 | 0.0373          | 0.9852 | 0.7066 |
| 0.0327        | 28.99 | 10800 | 0.0374          | 0.9849 | 0.7098 |


### Framework versions

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