
<!-- 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-xlsr-mecita-coraa-portuguese-all-clean-08

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: 0.1390
- Wer: 0.0887
- Cer: 0.0236

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 24.6865       | 1.0   | 67   | 3.4264          | 1.0    | 1.0    |
| 7.5805        | 2.0   | 134  | 2.9809          | 1.0    | 1.0    |
| 3.0234        | 3.0   | 201  | 2.9417          | 1.0    | 1.0    |
| 3.0234        | 4.0   | 268  | 2.8992          | 1.0    | 1.0    |
| 2.9257        | 5.0   | 335  | 2.8742          | 1.0    | 1.0    |
| 2.8778        | 6.0   | 402  | 2.7083          | 1.0    | 1.0    |
| 2.8778        | 7.0   | 469  | 1.3587          | 1.0    | 0.3296 |
| 2.1565        | 8.0   | 536  | 0.5632          | 0.2596 | 0.0630 |
| 0.937         | 9.0   | 603  | 0.4067          | 0.1967 | 0.0506 |
| 0.937         | 10.0  | 670  | 0.3297          | 0.1791 | 0.0460 |
| 0.602         | 11.0  | 737  | 0.2770          | 0.1618 | 0.0412 |
| 0.4956        | 12.0  | 804  | 0.2457          | 0.1496 | 0.0384 |
| 0.4956        | 13.0  | 871  | 0.2290          | 0.1369 | 0.0356 |
| 0.4144        | 14.0  | 938  | 0.2095          | 0.1273 | 0.0336 |
| 0.3712        | 15.0  | 1005 | 0.2069          | 0.1210 | 0.0320 |
| 0.3712        | 16.0  | 1072 | 0.1987          | 0.1163 | 0.0305 |
| 0.3271        | 17.0  | 1139 | 0.1910          | 0.1140 | 0.0303 |
| 0.3092        | 18.0  | 1206 | 0.1860          | 0.1103 | 0.0289 |
| 0.3092        | 19.0  | 1273 | 0.1748          | 0.1024 | 0.0281 |
| 0.2977        | 20.0  | 1340 | 0.1702          | 0.1034 | 0.0279 |
| 0.2865        | 21.0  | 1407 | 0.1631          | 0.1024 | 0.0274 |
| 0.2865        | 22.0  | 1474 | 0.1664          | 0.1004 | 0.0269 |
| 0.2463        | 23.0  | 1541 | 0.1617          | 0.1014 | 0.0276 |
| 0.2447        | 24.0  | 1608 | 0.1594          | 0.0967 | 0.0264 |
| 0.2447        | 25.0  | 1675 | 0.1516          | 0.0984 | 0.0262 |
| 0.2323        | 26.0  | 1742 | 0.1555          | 0.0974 | 0.0264 |
| 0.2229        | 27.0  | 1809 | 0.1487          | 0.0964 | 0.0261 |
| 0.2229        | 28.0  | 1876 | 0.1499          | 0.0967 | 0.0263 |
| 0.2015        | 29.0  | 1943 | 0.1474          | 0.1000 | 0.0270 |
| 0.1986        | 30.0  | 2010 | 0.1483          | 0.0917 | 0.0256 |
| 0.1986        | 31.0  | 2077 | 0.1473          | 0.0957 | 0.0259 |
| 0.1958        | 32.0  | 2144 | 0.1469          | 0.0954 | 0.0260 |
| 0.2034        | 33.0  | 2211 | 0.1475          | 0.0927 | 0.0251 |
| 0.2034        | 34.0  | 2278 | 0.1490          | 0.0931 | 0.0256 |
| 0.1947        | 35.0  | 2345 | 0.1483          | 0.0917 | 0.0249 |
| 0.1961        | 36.0  | 2412 | 0.1436          | 0.0924 | 0.0249 |
| 0.1961        | 37.0  | 2479 | 0.1479          | 0.0924 | 0.0252 |
| 0.181         | 38.0  | 2546 | 0.1442          | 0.0964 | 0.0253 |
| 0.1732        | 39.0  | 2613 | 0.1456          | 0.0937 | 0.0249 |
| 0.1732        | 40.0  | 2680 | 0.1427          | 0.0914 | 0.0249 |
| 0.174         | 41.0  | 2747 | 0.1448          | 0.0944 | 0.0250 |
| 0.1694        | 42.0  | 2814 | 0.1433          | 0.0911 | 0.0241 |
| 0.1694        | 43.0  | 2881 | 0.1421          | 0.0877 | 0.0233 |
| 0.1469        | 44.0  | 2948 | 0.1432          | 0.0907 | 0.0241 |
| 0.1665        | 45.0  | 3015 | 0.1410          | 0.0964 | 0.0250 |
| 0.1665        | 46.0  | 3082 | 0.1423          | 0.0924 | 0.0251 |
| 0.1662        | 47.0  | 3149 | 0.1422          | 0.0897 | 0.0239 |
| 0.154         | 48.0  | 3216 | 0.1408          | 0.0931 | 0.0245 |
| 0.154         | 49.0  | 3283 | 0.1451          | 0.0904 | 0.0242 |
| 0.1492        | 50.0  | 3350 | 0.1395          | 0.0911 | 0.0242 |
| 0.1532        | 51.0  | 3417 | 0.1390          | 0.0887 | 0.0236 |
| 0.1532        | 52.0  | 3484 | 0.1442          | 0.0941 | 0.0243 |
| 0.1442        | 53.0  | 3551 | 0.1429          | 0.0941 | 0.0241 |
| 0.1608        | 54.0  | 3618 | 0.1396          | 0.0897 | 0.0239 |
| 0.1608        | 55.0  | 3685 | 0.1427          | 0.0917 | 0.0240 |
| 0.1532        | 56.0  | 3752 | 0.1455          | 0.0897 | 0.0238 |
| 0.1376        | 57.0  | 3819 | 0.1425          | 0.0901 | 0.0239 |
| 0.1376        | 58.0  | 3886 | 0.1466          | 0.0891 | 0.0240 |
| 0.1327        | 59.0  | 3953 | 0.1422          | 0.0844 | 0.0232 |
| 0.1435        | 60.0  | 4020 | 0.1454          | 0.0901 | 0.0236 |
| 0.1435        | 61.0  | 4087 | 0.1399          | 0.0867 | 0.0234 |
| 0.1344        | 62.0  | 4154 | 0.1396          | 0.0874 | 0.0235 |
| 0.1382        | 63.0  | 4221 | 0.1403          | 0.0867 | 0.0232 |
| 0.1382        | 64.0  | 4288 | 0.1443          | 0.0871 | 0.0231 |
| 0.1303        | 65.0  | 4355 | 0.1413          | 0.0841 | 0.0225 |
| 0.1369        | 66.0  | 4422 | 0.1449          | 0.0877 | 0.0233 |
| 0.1369        | 67.0  | 4489 | 0.1444          | 0.0884 | 0.0231 |
| 0.1352        | 68.0  | 4556 | 0.1416          | 0.0887 | 0.0236 |
| 0.1493        | 69.0  | 4623 | 0.1437          | 0.0907 | 0.0247 |
| 0.1493        | 70.0  | 4690 | 0.1494          | 0.0907 | 0.0239 |
| 0.1186        | 71.0  | 4757 | 0.1460          | 0.0897 | 0.0239 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xlsr-mecita-coraa-portuguese-all-clean-08", "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-mecita-coraa-portuguese-all-clean-08
========================================================


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: 0.1390
* Wer: 0.0887
* Cer: 0.0236


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 4.28.0
* Pytorch 2.0.0+cu117
* 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 4.28.0
* Pytorch 2.0.0+cu117
* 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 4.28.0
* Pytorch 2.0.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3