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# wav2vec2-large-xlsr-mecita-coraa-portuguese-all-clean-07

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: 0.1190
- Wer: 0.0838
- Cer: 0.0235

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 26.9545       | 1.0   | 67   | 3.3218          | 1.0    | 1.0    |
| 6.7922        | 2.0   | 134  | 2.9660          | 1.0    | 1.0    |
| 2.9975        | 3.0   | 201  | 2.9543          | 1.0    | 1.0    |
| 2.9975        | 4.0   | 268  | 2.9085          | 1.0    | 1.0    |
| 2.9164        | 5.0   | 335  | 2.8689          | 1.0    | 1.0    |
| 2.8317        | 6.0   | 402  | 2.4003          | 0.9993 | 0.8377 |
| 2.8317        | 7.0   | 469  | 0.8135          | 0.4399 | 0.1061 |
| 1.665         | 8.0   | 536  | 0.4696          | 0.2409 | 0.0607 |
| 0.8096        | 9.0   | 603  | 0.3550          | 0.2042 | 0.0527 |
| 0.8096        | 10.0  | 670  | 0.2970          | 0.1890 | 0.0482 |
| 0.6279        | 11.0  | 737  | 0.2574          | 0.1616 | 0.0428 |
| 0.4796        | 12.0  | 804  | 0.2268          | 0.1568 | 0.0409 |
| 0.4796        | 13.0  | 871  | 0.2154          | 0.1488 | 0.0400 |
| 0.4053        | 14.0  | 938  | 0.1954          | 0.1340 | 0.0358 |
| 0.3627        | 15.0  | 1005 | 0.1850          | 0.1274 | 0.0345 |
| 0.3627        | 16.0  | 1072 | 0.1694          | 0.1177 | 0.0312 |
| 0.3498        | 17.0  | 1139 | 0.1631          | 0.1094 | 0.0299 |
| 0.2956        | 18.0  | 1206 | 0.1555          | 0.1056 | 0.0287 |
| 0.2956        | 19.0  | 1273 | 0.1522          | 0.1035 | 0.0290 |
| 0.2792        | 20.0  | 1340 | 0.1527          | 0.1076 | 0.0296 |
| 0.2767        | 21.0  | 1407 | 0.1453          | 0.1014 | 0.0276 |
| 0.2767        | 22.0  | 1474 | 0.1433          | 0.1031 | 0.0287 |
| 0.2511        | 23.0  | 1541 | 0.1396          | 0.0969 | 0.0273 |
| 0.2427        | 24.0  | 1608 | 0.1364          | 0.0973 | 0.0270 |
| 0.2427        | 25.0  | 1675 | 0.1346          | 0.0962 | 0.0261 |
| 0.2286        | 26.0  | 1742 | 0.1382          | 0.0931 | 0.0265 |
| 0.2202        | 27.0  | 1809 | 0.1331          | 0.0959 | 0.0261 |
| 0.2202        | 28.0  | 1876 | 0.1299          | 0.0917 | 0.0257 |
| 0.2363        | 29.0  | 1943 | 0.1260          | 0.0907 | 0.0251 |
| 0.1919        | 30.0  | 2010 | 0.1262          | 0.0893 | 0.0248 |
| 0.1919        | 31.0  | 2077 | 0.1260          | 0.0907 | 0.0254 |
| 0.1957        | 32.0  | 2144 | 0.1241          | 0.0907 | 0.0248 |
| 0.1969        | 33.0  | 2211 | 0.1254          | 0.0924 | 0.0248 |
| 0.1969        | 34.0  | 2278 | 0.1256          | 0.0886 | 0.0248 |
| 0.2182        | 35.0  | 2345 | 0.1228          | 0.0872 | 0.0248 |
| 0.1871        | 36.0  | 2412 | 0.1211          | 0.0872 | 0.0235 |
| 0.1871        | 37.0  | 2479 | 0.1231          | 0.0893 | 0.0245 |
| 0.1656        | 38.0  | 2546 | 0.1219          | 0.0886 | 0.0244 |
| 0.1678        | 39.0  | 2613 | 0.1190          | 0.0838 | 0.0235 |
| 0.1678        | 40.0  | 2680 | 0.1273          | 0.0907 | 0.0254 |
| 0.191         | 41.0  | 2747 | 0.1207          | 0.0869 | 0.0234 |
| 0.1772        | 42.0  | 2814 | 0.1231          | 0.0831 | 0.0235 |
| 0.1772        | 43.0  | 2881 | 0.1217          | 0.0876 | 0.0243 |
| 0.1786        | 44.0  | 2948 | 0.1244          | 0.0879 | 0.0244 |
| 0.1655        | 45.0  | 3015 | 0.1224          | 0.0876 | 0.0241 |
| 0.1655        | 46.0  | 3082 | 0.1254          | 0.0876 | 0.0244 |
| 0.1581        | 47.0  | 3149 | 0.1236          | 0.0907 | 0.0249 |
| 0.1567        | 48.0  | 3216 | 0.1208          | 0.0879 | 0.0241 |
| 0.1567        | 49.0  | 3283 | 0.1257          | 0.0914 | 0.0250 |
| 0.1489        | 50.0  | 3350 | 0.1221          | 0.0897 | 0.0252 |
| 0.1644        | 51.0  | 3417 | 0.1217          | 0.0869 | 0.0243 |
| 0.1644        | 52.0  | 3484 | 0.1245          | 0.0910 | 0.0253 |
| 0.1468        | 53.0  | 3551 | 0.1195          | 0.0862 | 0.0237 |
| 0.1461        | 54.0  | 3618 | 0.1198          | 0.0869 | 0.0235 |
| 0.1461        | 55.0  | 3685 | 0.1192          | 0.0879 | 0.0243 |
| 0.1435        | 56.0  | 3752 | 0.1242          | 0.0862 | 0.0242 |
| 0.1436        | 57.0  | 3819 | 0.1211          | 0.0893 | 0.0246 |
| 0.1436        | 58.0  | 3886 | 0.1230          | 0.0855 | 0.0243 |
| 0.1462        | 59.0  | 3953 | 0.1222          | 0.0897 | 0.0243 |


### 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-07", "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-07
========================================================


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: 0.1190
* Wer: 0.0838
* Cer: 0.0235


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