---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-lg
  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. -->

# wav2vec2-large-xls-r-300m-lg

This model is a fine-tuned version of [Alvin-Nahabwe/wav2vec2-large-xls-r-300m-gn](https://huggingface.co/Alvin-Nahabwe/wav2vec2-large-xls-r-300m-gn) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2283
- Wer: 0.1569

## 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: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 22
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2883        | 1.39  | 400  | 0.2180          | 0.2128 |
| 0.2603        | 2.78  | 800  | 0.2108          | 0.2082 |
| 0.2341        | 4.17  | 1200 | 0.2127          | 0.2085 |
| 0.2194        | 5.56  | 1600 | 0.2004          | 0.2050 |
| 0.1846        | 6.95  | 2000 | 0.1961          | 0.1898 |
| 0.1627        | 8.34  | 2400 | 0.1919          | 0.1779 |
| 0.1464        | 9.75  | 2800 | 0.1867          | 0.1677 |
| 0.1273        | 11.14 | 3200 | 0.1949          | 0.1710 |
| 0.1153        | 12.53 | 3600 | 0.1965          | 0.1639 |
| 0.1006        | 13.93 | 4000 | 0.1983          | 0.1603 |
| 0.1056        | 15.32 | 4400 | 0.2159          | 0.1686 |
| 0.1011        | 16.71 | 4800 | 0.2104          | 0.1663 |
| 0.0895        | 18.1  | 5200 | 0.2211          | 0.1634 |
| 0.0818        | 19.49 | 5600 | 0.2234          | 0.1610 |
| 0.0778        | 20.88 | 6000 | 0.2283          | 0.1569 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3