---
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: 0.9852694387469699
---

<!-- 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: 0.0359
- Wer: 0.9853
- Cer: 0.7143

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 3.8996        | 0.81  | 400   | 0.7268          | 1.0008 | 0.7672 |
| 0.5216        | 1.61  | 800   | 0.2765          | 1.0171 | 0.7602 |
| 0.3112        | 2.42  | 1200  | 0.1712          | 0.9965 | 0.7335 |
| 0.2343        | 3.23  | 1600  | 0.1169          | 0.9984 | 0.7262 |
| 0.1911        | 4.03  | 2000  | 0.0970          | 0.9970 | 0.7447 |
| 0.1625        | 4.84  | 2400  | 0.0834          | 0.9941 | 0.7245 |
| 0.1471        | 5.65  | 2800  | 0.0771          | 0.9936 | 0.7239 |
| 0.1301        | 6.45  | 3200  | 0.0645          | 0.9940 | 0.7330 |
| 0.1241        | 7.26  | 3600  | 0.0621          | 0.9912 | 0.7208 |
| 0.1128        | 8.06  | 4000  | 0.0672          | 0.9892 | 0.7188 |
| 0.1035        | 8.87  | 4400  | 0.0531          | 0.9895 | 0.7332 |
| 0.0993        | 9.68  | 4800  | 0.0541          | 0.9912 | 0.7374 |
| 0.0917        | 10.48 | 5200  | 0.0516          | 0.9883 | 0.7276 |
| 0.0879        | 11.29 | 5600  | 0.0507          | 0.9841 | 0.7246 |
| 0.0836        | 12.1  | 6000  | 0.0490          | 0.9858 | 0.7335 |
| 0.0767        | 12.9  | 6400  | 0.0464          | 0.9844 | 0.7231 |
| 0.0744        | 13.71 | 6800  | 0.0458          | 0.9855 | 0.7170 |
| 0.0695        | 14.52 | 7200  | 0.0506          | 0.9893 | 0.7145 |
| 0.0676        | 15.32 | 7600  | 0.0443          | 0.9892 | 0.7151 |
| 0.0621        | 16.13 | 8000  | 0.0457          | 0.9831 | 0.7188 |
| 0.0593        | 16.94 | 8400  | 0.0437          | 0.9905 | 0.7251 |
| 0.0558        | 17.74 | 8800  | 0.0419          | 0.9881 | 0.7160 |
| 0.0539        | 18.55 | 9200  | 0.0403          | 0.9897 | 0.7128 |
| 0.0509        | 19.35 | 9600  | 0.0435          | 0.9853 | 0.7195 |
| 0.0482        | 20.16 | 10000 | 0.0451          | 0.9863 | 0.7170 |
| 0.0452        | 20.97 | 10400 | 0.0397          | 0.9874 | 0.7128 |
| 0.0438        | 21.77 | 10800 | 0.0378          | 0.9874 | 0.7108 |
| 0.0419        | 22.58 | 11200 | 0.0394          | 0.9881 | 0.7096 |
| 0.0389        | 23.39 | 11600 | 0.0412          | 0.9874 | 0.7105 |
| 0.0377        | 24.19 | 12000 | 0.0388          | 0.9847 | 0.7180 |
| 0.0362        | 25.0  | 12400 | 0.0365          | 0.9848 | 0.7149 |
| 0.0336        | 25.81 | 12800 | 0.0363          | 0.9840 | 0.7144 |
| 0.0315        | 26.61 | 13200 | 0.0366          | 0.9855 | 0.7138 |
| 0.031         | 27.42 | 13600 | 0.0381          | 0.9864 | 0.7171 |
| 0.0303        | 28.23 | 14000 | 0.0363          | 0.9857 | 0.7145 |
| 0.0276        | 29.03 | 14400 | 0.0365          | 0.9854 | 0.7136 |
| 0.0282        | 29.84 | 14800 | 0.0359          | 0.9853 | 0.7143 |


### Framework versions

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