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# wav2vec2-large-xls-r-300m-guarani-small-wb

This model is a fine-tuned version of [glob-asr/wav2vec2-large-xls-r-300m-guarani-small](https://huggingface.co/glob-asr/wav2vec2-large-xls-r-300m-guarani-small) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1622
- Wer: 0.2446
- Cer: 0.0368

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.1818        | 0.32  | 10   | 0.1196          | 0.2146 | 0.0305 |
| 0.2953        | 0.65  | 20   | 0.1801          | 0.3090 | 0.0426 |
| 0.2941        | 0.97  | 30   | 0.1935          | 0.3090 | 0.0420 |
| 0.2786        | 1.29  | 40   | 0.1899          | 0.3305 | 0.0483 |
| 0.2665        | 1.61  | 50   | 0.1716          | 0.3176 | 0.0454 |
| 0.2752        | 1.94  | 60   | 0.1895          | 0.3948 | 0.0564 |
| 0.2482        | 2.26  | 70   | 0.1753          | 0.3176 | 0.0449 |
| 0.2486        | 2.58  | 80   | 0.1501          | 0.2747 | 0.0403 |
| 0.2878        | 2.9   | 90   | 0.1890          | 0.3348 | 0.0529 |
| 0.2539        | 3.23  | 100  | 0.2076          | 0.4635 | 0.0610 |
| 0.2069        | 3.55  | 110  | 0.1711          | 0.3476 | 0.0466 |
| 0.2262        | 3.87  | 120  | 0.1839          | 0.3605 | 0.0500 |
| 0.2032        | 4.19  | 130  | 0.1724          | 0.3391 | 0.0489 |
| 0.1997        | 4.52  | 140  | 0.1498          | 0.2704 | 0.0414 |
| 0.2216        | 4.84  | 150  | 0.1531          | 0.3047 | 0.0472 |
| 0.2294        | 5.16  | 160  | 0.1882          | 0.3176 | 0.0500 |
| 0.2305        | 5.48  | 170  | 0.1799          | 0.3176 | 0.0483 |
| 0.2052        | 5.81  | 180  | 0.1645          | 0.3262 | 0.0477 |
| 0.2192        | 6.13  | 190  | 0.1439          | 0.2060 | 0.0339 |
| 0.1844        | 6.45  | 200  | 0.1557          | 0.2918 | 0.0403 |
| 0.1803        | 6.77  | 210  | 0.1664          | 0.3004 | 0.0426 |
| 0.1831        | 7.1   | 220  | 0.1780          | 0.3176 | 0.0477 |
| 0.1618        | 7.42  | 230  | 0.1671          | 0.2661 | 0.0437 |
| 0.1528        | 7.74  | 240  | 0.2108          | 0.3176 | 0.0506 |
| 0.1335        | 8.06  | 250  | 0.1677          | 0.2575 | 0.0408 |
| 0.1736        | 8.39  | 260  | 0.1581          | 0.3004 | 0.0460 |
| 0.1607        | 8.71  | 270  | 0.1529          | 0.3047 | 0.0403 |
| 0.1451        | 9.03  | 280  | 0.1666          | 0.2747 | 0.0408 |
| 0.1534        | 9.35  | 290  | 0.1722          | 0.2833 | 0.0437 |
| 0.1567        | 9.68  | 300  | 0.1747          | 0.2918 | 0.0397 |
| 0.1356        | 10.0  | 310  | 0.1659          | 0.2961 | 0.0443 |
| 0.1248        | 10.32 | 320  | 0.1752          | 0.3348 | 0.0449 |
| 0.149         | 10.65 | 330  | 0.1792          | 0.3348 | 0.0449 |
| 0.1471        | 10.97 | 340  | 0.1843          | 0.3391 | 0.0460 |
| 0.1564        | 11.29 | 350  | 0.2015          | 0.3433 | 0.0460 |
| 0.1597        | 11.61 | 360  | 0.1798          | 0.2618 | 0.0380 |
| 0.161         | 11.94 | 370  | 0.1716          | 0.2747 | 0.0374 |
| 0.1481        | 12.26 | 380  | 0.1776          | 0.2747 | 0.0397 |
| 0.1168        | 12.58 | 390  | 0.1900          | 0.2961 | 0.0454 |
| 0.1173        | 12.9  | 400  | 0.1987          | 0.3090 | 0.0454 |
| 0.1245        | 13.23 | 410  | 0.1710          | 0.2918 | 0.0408 |
| 0.1118        | 13.55 | 420  | 0.1808          | 0.3047 | 0.0431 |
| 0.1111        | 13.87 | 430  | 0.1893          | 0.2747 | 0.0403 |
| 0.1041        | 14.19 | 440  | 0.1876          | 0.2918 | 0.0431 |
| 0.1152        | 14.52 | 450  | 0.1800          | 0.2790 | 0.0408 |
| 0.107         | 14.84 | 460  | 0.1717          | 0.2747 | 0.0385 |
| 0.1139        | 15.16 | 470  | 0.1652          | 0.2704 | 0.0391 |
| 0.0922        | 15.48 | 480  | 0.1659          | 0.2618 | 0.0391 |
| 0.101         | 15.81 | 490  | 0.1610          | 0.2489 | 0.0362 |
| 0.0835        | 16.13 | 500  | 0.1584          | 0.2403 | 0.0362 |
| 0.1251        | 16.45 | 510  | 0.1601          | 0.2575 | 0.0380 |
| 0.0888        | 16.77 | 520  | 0.1632          | 0.2661 | 0.0380 |
| 0.0968        | 17.1  | 530  | 0.1674          | 0.2661 | 0.0385 |
| 0.1105        | 17.42 | 540  | 0.1629          | 0.2833 | 0.0391 |
| 0.0914        | 17.74 | 550  | 0.1623          | 0.3090 | 0.0408 |
| 0.0843        | 18.06 | 560  | 0.1611          | 0.3004 | 0.0408 |
| 0.0861        | 18.39 | 570  | 0.1583          | 0.2661 | 0.0385 |
| 0.0861        | 18.71 | 580  | 0.1579          | 0.2618 | 0.0385 |
| 0.0678        | 19.03 | 590  | 0.1585          | 0.2661 | 0.0374 |
| 0.0934        | 19.35 | 600  | 0.1613          | 0.2489 | 0.0368 |
| 0.0976        | 19.68 | 610  | 0.1617          | 0.2446 | 0.0368 |
| 0.0799        | 20.0  | 620  | 0.1622          | 0.2446 | 0.0368 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-guarani-small-wb", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-large-xls-r-300m-guarani-small-wb
==========================================


This model is a fine-tuned version of glob-asr/wav2vec2-large-xls-r-300m-guarani-small on the common\_voice dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1622
* Wer: 0.2446
* Cer: 0.0368


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: 0.0002
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10
* num\_epochs: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10
* num\_epochs: 20
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1