---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-grain
  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-grain

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the Grain gender-balanced dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1510
- Wer: 0.0762

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.1496        | 2.5   | 400   | 0.7656          | 0.8096 |
| 0.2914        | 5.0   | 800   | 0.3202          | 0.3544 |
| 0.1152        | 7.5   | 1200  | 0.2666          | 0.2894 |
| 0.0722        | 10.0  | 1600  | 0.2834          | 0.2458 |
| 0.0528        | 12.5  | 2000  | 0.2475          | 0.2159 |
| 0.0423        | 15.0  | 2400  | 0.2430          | 0.1971 |
| 0.0334        | 17.5  | 2800  | 0.2250          | 0.1925 |
| 0.0288        | 20.0  | 3200  | 0.2119          | 0.1779 |
| 0.0253        | 22.5  | 3600  | 0.2226          | 0.1711 |
| 0.0214        | 25.0  | 4000  | 0.2224          | 0.1685 |
| 0.0217        | 27.5  | 4400  | 0.2098          | 0.1516 |
| 0.0182        | 30.0  | 4800  | 0.2153          | 0.1716 |
| 0.0173        | 32.5  | 5200  | 0.1925          | 0.1451 |
| 0.0137        | 35.0  | 5600  | 0.2241          | 0.1469 |
| 0.0118        | 37.5  | 6000  | 0.2013          | 0.1515 |
| 0.0133        | 40.0  | 6400  | 0.1990          | 0.1332 |
| 0.0125        | 42.5  | 6800  | 0.2146          | 0.1502 |
| 0.0103        | 45.0  | 7200  | 0.2191          | 0.1317 |
| 0.0089        | 47.5  | 7600  | 0.1869          | 0.1246 |
| 0.0091        | 50.0  | 8000  | 0.1734          | 0.1251 |
| 0.008         | 52.5  | 8400  | 0.2008          | 0.1290 |
| 0.0071        | 55.0  | 8800  | 0.1828          | 0.1260 |
| 0.0064        | 57.5  | 9200  | 0.1689          | 0.1081 |
| 0.0061        | 60.0  | 9600  | 0.1676          | 0.1111 |
| 0.0051        | 62.5  | 10000 | 0.1707          | 0.1048 |
| 0.0056        | 65.0  | 10400 | 0.1741          | 0.1131 |
| 0.0046        | 67.5  | 10800 | 0.1836          | 0.1034 |
| 0.0036        | 70.0  | 11200 | 0.1655          | 0.0966 |
| 0.0037        | 72.5  | 11600 | 0.1734          | 0.1047 |
| 0.003         | 75.0  | 12000 | 0.1718          | 0.0975 |
| 0.0032        | 77.5  | 12400 | 0.1598          | 0.0986 |
| 0.0023        | 80.0  | 12800 | 0.1640          | 0.0966 |
| 0.0019        | 82.5  | 13200 | 0.1701          | 0.0862 |
| 0.0015        | 85.0  | 13600 | 0.1643          | 0.0854 |
| 0.0016        | 87.5  | 14000 | 0.1470          | 0.0823 |
| 0.0014        | 90.0  | 14400 | 0.1589          | 0.0838 |
| 0.0011        | 92.5  | 14800 | 0.1610          | 0.0834 |
| 0.0013        | 95.0  | 15200 | 0.1457          | 0.0788 |
| 0.001         | 97.5  | 15600 | 0.1537          | 0.0762 |
| 0.001         | 100.0 | 16000 | 0.1510          | 0.0762 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1