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

# jako-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: 0.9486
- Cer: 0.2606

## 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: 2
- total_train_batch_size: 32
- 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: 0.03
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5667        | 1.14  | 1000  | 2.2323          | 0.5188 |
| 1.5569        | 2.28  | 2000  | 1.3106          | 0.3527 |
| 1.2238        | 3.43  | 3000  | 1.1109          | 0.3099 |
| 1.0593        | 4.57  | 4000  | 1.0390          | 0.2891 |
| 0.9658        | 5.71  | 5000  | 0.9731          | 0.2918 |
| 0.8796        | 6.85  | 6000  | 0.9479          | 0.2696 |
| 0.8022        | 8.0   | 7000  | 0.9331          | 0.2710 |
| 0.7392        | 9.14  | 8000  | 0.9252          | 0.2746 |
| 0.6694        | 10.28 | 9000  | 0.9318          | 0.2590 |
| 0.5977        | 11.42 | 10000 | 0.9349          | 0.2674 |
| 0.5484        | 12.56 | 11000 | 0.9409          | 0.2555 |
| 0.5154        | 13.71 | 12000 | 0.9510          | 0.2719 |
| 0.4767        | 14.85 | 13000 | 0.9556          | 0.2624 |
| 0.4536        | 15.99 | 14000 | 0.9850          | 0.2684 |
| 0.4195        | 17.13 | 15000 | 0.9894          | 0.2590 |
| 0.3937        | 18.28 | 16000 | 1.0197          | 0.2698 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1