---
license: apache-2.0
base_model: facebook/wav2vec2-large
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: Check_Model_1
  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: 0.37479022934924483
---

<!-- 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. -->

# Check_Model_1

This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5522
- Wer: 0.3748
- Cer: 0.1158

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 2.1839        | 3.23  | 400  | 0.8796          | 0.7306 | 0.2332 |
| 0.6388        | 6.45  | 800  | 0.8702          | 0.6410 | 0.2200 |
| 0.4695        | 9.68  | 1200 | 0.7064          | 0.5360 | 0.1632 |
| 0.3659        | 12.9  | 1600 | 0.5814          | 0.5211 | 0.1662 |
| 0.285         | 16.13 | 2000 | 0.6394          | 0.5041 | 0.1663 |
| 0.2254        | 19.35 | 2400 | 0.5889          | 0.4428 | 0.1405 |
| 0.1801        | 22.58 | 2800 | 0.5712          | 0.4013 | 0.1182 |
| 0.1392        | 25.81 | 3200 | 0.5914          | 0.3934 | 0.1177 |
| 0.1051        | 29.03 | 3600 | 0.5522          | 0.3748 | 0.1158 |


### Framework versions

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