---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Model_G_2
  results: []
---

<!-- 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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7332
- Wer: 1.0098
- Cer: 0.7490

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 3.5212        | 2.57  | 400  | 0.7741          | 1.0236 | 0.7838 |
| 0.3158        | 5.14  | 800  | 0.6119          | 1.0085 | 0.7600 |
| 0.1522        | 7.72  | 1200 | 0.6402          | 1.0215 | 0.7521 |
| 0.102         | 10.29 | 1600 | 0.6226          | 1.0134 | 0.7540 |
| 0.0752        | 12.86 | 2000 | 0.6474          | 1.0365 | 0.7501 |
| 0.0627        | 15.43 | 2400 | 0.6617          | 1.0169 | 0.7503 |
| 0.0535        | 18.01 | 2800 | 0.6818          | 1.0116 | 0.7495 |
| 0.0432        | 20.58 | 3200 | 0.7056          | 1.0125 | 0.7536 |
| 0.0383        | 23.15 | 3600 | 0.6953          | 1.0096 | 0.7448 |
| 0.0347        | 25.72 | 4000 | 0.7217          | 1.0202 | 0.7457 |
| 0.0301        | 28.3  | 4400 | 0.7332          | 1.0098 | 0.7490 |


### Framework versions

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