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# wav2vec2-large-xlsr-mec-ita-coraa-portuguese-all-09

This model is a fine-tuned version of [Edresson/wav2vec2-large-xlsr-coraa-portuguese](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1518
- Wer: 0.0933
- Cer: 0.0305

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 29.5822       | 1.0   | 86   | 3.2519          | 1.0    | 1.0    |
| 7.4163        | 2.0   | 172  | 2.9510          | 1.0    | 1.0    |
| 3.0543        | 3.0   | 258  | 2.9271          | 1.0    | 1.0    |
| 2.9256        | 4.0   | 344  | 2.8872          | 1.0    | 1.0    |
| 2.8789        | 5.0   | 430  | 2.4985          | 0.9978 | 0.9154 |
| 2.252         | 6.0   | 516  | 0.8675          | 0.6029 | 0.1494 |
| 1.0699        | 7.0   | 602  | 0.4857          | 0.2424 | 0.0681 |
| 1.0699        | 8.0   | 688  | 0.3746          | 0.1884 | 0.0568 |
| 0.7411        | 9.0   | 774  | 0.3188          | 0.1704 | 0.0520 |
| 0.5815        | 10.0  | 860  | 0.2876          | 0.1653 | 0.0497 |
| 0.5181        | 11.0  | 946  | 0.2563          | 0.1513 | 0.0467 |
| 0.4439        | 12.0  | 1032 | 0.2341          | 0.1504 | 0.0448 |
| 0.3882        | 13.0  | 1118 | 0.2330          | 0.1441 | 0.0457 |
| 0.3642        | 14.0  | 1204 | 0.2141          | 0.1328 | 0.0417 |
| 0.3642        | 15.0  | 1290 | 0.2043          | 0.1186 | 0.0384 |
| 0.3497        | 16.0  | 1376 | 0.1955          | 0.1178 | 0.0380 |
| 0.309         | 17.0  | 1462 | 0.1921          | 0.1145 | 0.0373 |
| 0.291         | 18.0  | 1548 | 0.1869          | 0.1157 | 0.0361 |
| 0.2904        | 19.0  | 1634 | 0.1778          | 0.1111 | 0.0358 |
| 0.2961        | 20.0  | 1720 | 0.1739          | 0.1067 | 0.0352 |
| 0.2796        | 21.0  | 1806 | 0.1736          | 0.1108 | 0.0360 |
| 0.2796        | 22.0  | 1892 | 0.1685          | 0.1094 | 0.0355 |
| 0.2666        | 23.0  | 1978 | 0.1707          | 0.1092 | 0.0355 |
| 0.2404        | 24.0  | 2064 | 0.1724          | 0.1125 | 0.0358 |
| 0.2284        | 25.0  | 2150 | 0.1677          | 0.1077 | 0.0349 |
| 0.2254        | 26.0  | 2236 | 0.1650          | 0.1084 | 0.0342 |
| 0.2071        | 27.0  | 2322 | 0.1621          | 0.1010 | 0.0335 |
| 0.2107        | 28.0  | 2408 | 0.1613          | 0.1027 | 0.0337 |
| 0.2107        | 29.0  | 2494 | 0.1646          | 0.1048 | 0.0339 |
| 0.2133        | 30.0  | 2580 | 0.1639          | 0.0995 | 0.0323 |
| 0.2032        | 31.0  | 2666 | 0.1624          | 0.1002 | 0.0327 |
| 0.216         | 32.0  | 2752 | 0.1610          | 0.1017 | 0.0328 |
| 0.2075        | 33.0  | 2838 | 0.1593          | 0.0986 | 0.0319 |
| 0.1946        | 34.0  | 2924 | 0.1617          | 0.0983 | 0.0316 |
| 0.1731        | 35.0  | 3010 | 0.1626          | 0.0993 | 0.0320 |
| 0.1731        | 36.0  | 3096 | 0.1586          | 0.0998 | 0.0324 |
| 0.1763        | 37.0  | 3182 | 0.1594          | 0.0986 | 0.0318 |
| 0.1982        | 38.0  | 3268 | 0.1570          | 0.0993 | 0.0319 |
| 0.1877        | 39.0  | 3354 | 0.1560          | 0.0993 | 0.0316 |
| 0.1674        | 40.0  | 3440 | 0.1560          | 0.0986 | 0.0318 |
| 0.1582        | 41.0  | 3526 | 0.1548          | 0.0995 | 0.0314 |
| 0.1653        | 42.0  | 3612 | 0.1561          | 0.0957 | 0.0308 |
| 0.1653        | 43.0  | 3698 | 0.1570          | 0.0969 | 0.0311 |
| 0.1572        | 44.0  | 3784 | 0.1553          | 0.0961 | 0.0310 |
| 0.1693        | 45.0  | 3870 | 0.1568          | 0.0952 | 0.0308 |
| 0.1651        | 46.0  | 3956 | 0.1587          | 0.1    | 0.0318 |
| 0.1468        | 47.0  | 4042 | 0.1567          | 0.1012 | 0.0324 |
| 0.1592        | 48.0  | 4128 | 0.1572          | 0.0976 | 0.0313 |
| 0.1556        | 49.0  | 4214 | 0.1535          | 0.0949 | 0.0306 |
| 0.1431        | 50.0  | 4300 | 0.1560          | 0.0978 | 0.0314 |
| 0.1431        | 51.0  | 4386 | 0.1547          | 0.0937 | 0.0304 |
| 0.1461        | 52.0  | 4472 | 0.1542          | 0.0969 | 0.0304 |
| 0.1463        | 53.0  | 4558 | 0.1536          | 0.0954 | 0.0307 |
| 0.1447        | 54.0  | 4644 | 0.1561          | 0.0925 | 0.0301 |
| 0.1391        | 55.0  | 4730 | 0.1518          | 0.0933 | 0.0305 |
| 0.1422        | 56.0  | 4816 | 0.1558          | 0.0978 | 0.0311 |
| 0.1415        | 57.0  | 4902 | 0.1520          | 0.0945 | 0.0304 |
| 0.1415        | 58.0  | 4988 | 0.1555          | 0.0978 | 0.0310 |
| 0.1323        | 59.0  | 5074 | 0.1574          | 0.0933 | 0.0299 |
| 0.1294        | 60.0  | 5160 | 0.1569          | 0.0942 | 0.0304 |
| 0.1296        | 61.0  | 5246 | 0.1539          | 0.0945 | 0.0305 |
| 0.1349        | 62.0  | 5332 | 0.1533          | 0.0896 | 0.0298 |
| 0.1303        | 63.0  | 5418 | 0.1537          | 0.0906 | 0.0299 |
| 0.1426        | 64.0  | 5504 | 0.1551          | 0.0884 | 0.0293 |
| 0.1426        | 65.0  | 5590 | 0.1569          | 0.0923 | 0.0301 |
| 0.1231        | 66.0  | 5676 | 0.1553          | 0.0882 | 0.0295 |
| 0.1338        | 67.0  | 5762 | 0.1583          | 0.0889 | 0.0296 |
| 0.1249        | 68.0  | 5848 | 0.1567          | 0.0913 | 0.0300 |
| 0.1289        | 69.0  | 5934 | 0.1577          | 0.0933 | 0.0306 |
| 0.1228        | 70.0  | 6020 | 0.1537          | 0.0916 | 0.0304 |
| 0.1372        | 71.0  | 6106 | 0.1533          | 0.0930 | 0.0302 |
| 0.1372        | 72.0  | 6192 | 0.1562          | 0.0920 | 0.0305 |
| 0.1211        | 73.0  | 6278 | 0.1571          | 0.0906 | 0.0301 |
| 0.1211        | 74.0  | 6364 | 0.1557          | 0.0916 | 0.0302 |
| 0.1185        | 75.0  | 6450 | 0.1572          | 0.0889 | 0.0304 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xlsr-mec-ita-coraa-portuguese-all-09", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-large-xlsr-mec-ita-coraa-portuguese-all-09
===================================================


This model is a fine-tuned version of Edresson/wav2vec2-large-xlsr-coraa-portuguese on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1518
* Wer: 0.0933
* Cer: 0.0305


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: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3