---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- ./sample_speech.py
- generated_from_trainer
metrics:
- wer
model-index:
- name: en-xlsr
  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. -->

# en-xlsr

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5574
- Cer: 0.0835
- Wer: 0.1854

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.6992        | 2.79  | 600  | 0.4981          | 0.1370 | 0.3376 |
| 0.3394        | 5.58  | 1200 | 0.3934          | 0.1057 | 0.2467 |
| 0.2376        | 8.37  | 1800 | 0.4123          | 0.1015 | 0.2356 |
| 0.1877        | 11.16 | 2400 | 0.4269          | 0.0928 | 0.2136 |
| 0.1494        | 13.95 | 3000 | 0.4648          | 0.0922 | 0.2102 |
| 0.1186        | 16.74 | 3600 | 0.4835          | 0.0919 | 0.2058 |
| 0.0966        | 19.53 | 4200 | 0.4986          | 0.0875 | 0.1978 |
| 0.083         | 22.33 | 4800 | 0.5179          | 0.0862 | 0.1927 |
| 0.071         | 25.12 | 5400 | 0.5539          | 0.0857 | 0.1908 |
| 0.0648        | 27.91 | 6000 | 0.5583          | 0.0844 | 0.1870 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1