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# model-facebookptbrlarge

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53-portuguese](https://huggingface.co/facebook/wav2vec2-large-xlsr-53-portuguese) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2206
- Wer: 0.1322

## 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: 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: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.8975        | 0.29  | 400   | 0.4131          | 0.3336 |
| 0.5131        | 0.57  | 800   | 0.4103          | 0.3293 |
| 0.4846        | 0.86  | 1200  | 0.3493          | 0.3028 |
| 0.4174        | 1.14  | 1600  | 0.3055          | 0.2730 |
| 0.4105        | 1.43  | 2000  | 0.3283          | 0.3041 |
| 0.4028        | 1.72  | 2400  | 0.3539          | 0.3210 |
| 0.386         | 2.0   | 2800  | 0.2925          | 0.2690 |
| 0.3224        | 2.29  | 3200  | 0.2842          | 0.2665 |
| 0.3122        | 2.57  | 3600  | 0.2781          | 0.2472 |
| 0.3087        | 2.86  | 4000  | 0.2794          | 0.2692 |
| 0.2878        | 3.15  | 4400  | 0.2795          | 0.2537 |
| 0.2915        | 3.43  | 4800  | 0.2764          | 0.2478 |
| 0.2816        | 3.72  | 5200  | 0.2761          | 0.2366 |
| 0.283         | 4.0   | 5600  | 0.2641          | 0.2587 |
| 0.2448        | 4.29  | 6000  | 0.2489          | 0.2417 |
| 0.247         | 4.57  | 6400  | 0.2538          | 0.2422 |
| 0.25          | 4.86  | 6800  | 0.2660          | 0.2306 |
| 0.2256        | 5.15  | 7200  | 0.2477          | 0.2267 |
| 0.2225        | 5.43  | 7600  | 0.2364          | 0.2195 |
| 0.2217        | 5.72  | 8000  | 0.2319          | 0.2139 |
| 0.2272        | 6.0   | 8400  | 0.2489          | 0.2427 |
| 0.2016        | 6.29  | 8800  | 0.2404          | 0.2181 |
| 0.1973        | 6.58  | 9200  | 0.2532          | 0.2273 |
| 0.2101        | 6.86  | 9600  | 0.2590          | 0.2100 |
| 0.1946        | 7.15  | 10000 | 0.2414          | 0.2108 |
| 0.1845        | 7.43  | 10400 | 0.2485          | 0.2124 |
| 0.1861        | 7.72  | 10800 | 0.2405          | 0.2124 |
| 0.1851        | 8.01  | 11200 | 0.2449          | 0.2062 |
| 0.1587        | 8.29  | 11600 | 0.2510          | 0.2048 |
| 0.1694        | 8.58  | 12000 | 0.2290          | 0.2059 |
| 0.1637        | 8.86  | 12400 | 0.2376          | 0.2063 |
| 0.1594        | 9.15  | 12800 | 0.2307          | 0.1967 |
| 0.1537        | 9.44  | 13200 | 0.2274          | 0.2017 |
| 0.1498        | 9.72  | 13600 | 0.2322          | 0.2025 |
| 0.1516        | 10.01 | 14000 | 0.2323          | 0.1971 |
| 0.1336        | 10.29 | 14400 | 0.2249          | 0.1920 |
| 0.134         | 10.58 | 14800 | 0.2258          | 0.2055 |
| 0.138         | 10.86 | 15200 | 0.2250          | 0.1906 |
| 0.13          | 11.15 | 15600 | 0.2423          | 0.1920 |
| 0.1302        | 11.44 | 16000 | 0.2294          | 0.1849 |
| 0.1253        | 11.72 | 16400 | 0.2193          | 0.1889 |
| 0.1219        | 12.01 | 16800 | 0.2350          | 0.1869 |
| 0.1149        | 12.29 | 17200 | 0.2350          | 0.1903 |
| 0.1161        | 12.58 | 17600 | 0.2277          | 0.1899 |
| 0.1129        | 12.87 | 18000 | 0.2416          | 0.1855 |
| 0.1091        | 13.15 | 18400 | 0.2289          | 0.1815 |
| 0.1073        | 13.44 | 18800 | 0.2383          | 0.1799 |
| 0.1135        | 13.72 | 19200 | 0.2306          | 0.1819 |
| 0.1075        | 14.01 | 19600 | 0.2283          | 0.1742 |
| 0.0971        | 14.3  | 20000 | 0.2271          | 0.1851 |
| 0.0967        | 14.58 | 20400 | 0.2395          | 0.1809 |
| 0.1039        | 14.87 | 20800 | 0.2286          | 0.1808 |
| 0.0984        | 15.15 | 21200 | 0.2303          | 0.1821 |
| 0.0922        | 15.44 | 21600 | 0.2254          | 0.1745 |
| 0.0882        | 15.73 | 22000 | 0.2280          | 0.1836 |
| 0.0859        | 16.01 | 22400 | 0.2355          | 0.1779 |
| 0.0832        | 16.3  | 22800 | 0.2347          | 0.1740 |
| 0.0854        | 16.58 | 23200 | 0.2342          | 0.1739 |
| 0.0874        | 16.87 | 23600 | 0.2316          | 0.1719 |
| 0.0808        | 17.16 | 24000 | 0.2291          | 0.1730 |
| 0.0741        | 17.44 | 24400 | 0.2308          | 0.1674 |
| 0.0815        | 17.73 | 24800 | 0.2329          | 0.1655 |
| 0.0764        | 18.01 | 25200 | 0.2514          | 0.1711 |
| 0.0719        | 18.3  | 25600 | 0.2275          | 0.1578 |
| 0.0665        | 18.58 | 26000 | 0.2367          | 0.1614 |
| 0.0693        | 18.87 | 26400 | 0.2185          | 0.1593 |
| 0.0662        | 19.16 | 26800 | 0.2266          | 0.1678 |
| 0.0612        | 19.44 | 27200 | 0.2332          | 0.1602 |
| 0.0623        | 19.73 | 27600 | 0.2283          | 0.1670 |
| 0.0659        | 20.01 | 28000 | 0.2142          | 0.1626 |
| 0.0581        | 20.3  | 28400 | 0.2198          | 0.1646 |
| 0.063         | 20.59 | 28800 | 0.2251          | 0.1588 |
| 0.0618        | 20.87 | 29200 | 0.2186          | 0.1554 |
| 0.0549        | 21.16 | 29600 | 0.2251          | 0.1490 |
| 0.058         | 21.44 | 30000 | 0.2366          | 0.1559 |
| 0.0543        | 21.73 | 30400 | 0.2262          | 0.1535 |
| 0.0529        | 22.02 | 30800 | 0.2358          | 0.1519 |
| 0.053         | 22.3  | 31200 | 0.2198          | 0.1513 |
| 0.0552        | 22.59 | 31600 | 0.2234          | 0.1503 |
| 0.0492        | 22.87 | 32000 | 0.2191          | 0.1516 |
| 0.0488        | 23.16 | 32400 | 0.2321          | 0.1500 |
| 0.0479        | 23.45 | 32800 | 0.2152          | 0.1420 |
| 0.0453        | 23.73 | 33200 | 0.2202          | 0.1453 |
| 0.0485        | 24.02 | 33600 | 0.2235          | 0.1468 |
| 0.0451        | 24.3  | 34000 | 0.2192          | 0.1455 |
| 0.041         | 24.59 | 34400 | 0.2138          | 0.1438 |
| 0.0435        | 24.87 | 34800 | 0.2335          | 0.1423 |
| 0.0404        | 25.16 | 35200 | 0.2220          | 0.1409 |
| 0.0374        | 25.45 | 35600 | 0.2366          | 0.1437 |
| 0.0405        | 25.73 | 36000 | 0.2233          | 0.1428 |
| 0.0385        | 26.02 | 36400 | 0.2208          | 0.1414 |
| 0.0373        | 26.3  | 36800 | 0.2265          | 0.1420 |
| 0.0365        | 26.59 | 37200 | 0.2174          | 0.1402 |
| 0.037         | 26.88 | 37600 | 0.2249          | 0.1397 |
| 0.0379        | 27.16 | 38000 | 0.2173          | 0.1374 |
| 0.0354        | 27.45 | 38400 | 0.2212          | 0.1381 |
| 0.034         | 27.73 | 38800 | 0.2313          | 0.1364 |
| 0.0347        | 28.02 | 39200 | 0.2230          | 0.1356 |
| 0.0318        | 28.31 | 39600 | 0.2231          | 0.1357 |
| 0.0305        | 28.59 | 40000 | 0.2281          | 0.1366 |
| 0.0307        | 28.88 | 40400 | 0.2259          | 0.1342 |
| 0.0315        | 29.16 | 40800 | 0.2252          | 0.1332 |
| 0.0314        | 29.45 | 41200 | 0.2218          | 0.1328 |
| 0.0307        | 29.74 | 41600 | 0.2206          | 0.1322 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.8.1+cu111
- Datasets 2.2.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "model-facebookptbrlarge", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us 

model-facebookptbrlarge
=======================


This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53-portuguese on the common\_voice dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2206
* Wer: 0.1322


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: 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: 500
* num\_epochs: 30
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.8.1+cu111
* Datasets 2.2.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* 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: 500
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.8.1+cu111
* Datasets 2.2.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #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: 0.0003
* 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: 500
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.8.1+cu111
* Datasets 2.2.1
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #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: 0.0003
* 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: 500
* num\_epochs: 30
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.8.1+cu111
* Datasets 2.2.1
* Tokenizers 0.12.1