---
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: enko_xlsr_13p_run1
  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. -->

# enko_xlsr_13p_run1

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: 0.3042
- Wer: 0.1696

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.6595        | 1.0   | 7702  | 0.4495          | 0.2974 |
| 0.5717        | 2.0   | 15404 | 0.3982          | 0.2562 |
| 0.5134        | 3.0   | 23106 | 0.3769          | 0.2365 |
| 0.467         | 4.0   | 30808 | 0.3499          | 0.2203 |
| 0.4156        | 5.0   | 38510 | 0.3391          | 0.2116 |
| 0.379         | 6.0   | 46212 | 0.3327          | 0.1999 |
| 0.3475        | 7.0   | 53914 | 0.3127          | 0.1947 |
| 0.3105        | 8.0   | 61616 | 0.3081          | 0.1814 |
| 0.281         | 9.0   | 69318 | 0.3068          | 0.1742 |
| 0.2584        | 10.0  | 77020 | 0.3040          | 0.1713 |


### Framework versions

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