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# wav2vec2-large-xlsr-mecita-coraa-portuguese-all-05

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: 0.2174
- Wer: 0.1429
- Cer: 0.0430

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 28.1646       | 1.0   | 86   | 4.8610          | 0.9832 | 0.9803 |
| 9.4454        | 2.0   | 172  | 3.3327          | 0.9567 | 0.9034 |
| 4.3702        | 3.0   | 258  | 3.1962          | 1.0    | 1.0    |
| 4.398         | 4.0   | 344  | 2.9906          | 1.0    | 1.0    |
| 3.7462        | 5.0   | 430  | 2.9604          | 1.0    | 1.0    |
| 3.9079        | 6.0   | 516  | 2.9447          | 0.9659 | 0.9651 |
| 3.9602        | 7.0   | 602  | 2.8960          | 0.9591 | 0.9286 |
| 3.9602        | 8.0   | 688  | 2.8418          | 0.9555 | 0.8580 |
| 3.7183        | 9.0   | 774  | 2.8463          | 0.9516 | 0.8567 |
| 3.7229        | 10.0  | 860  | 2.9000          | 0.9706 | 0.8790 |
| 3.7056        | 11.0  | 946  | 2.7891          | 0.9747 | 0.8368 |
| 4.3909        | 12.0  | 1032 | 2.8128          | 0.9681 | 0.8091 |
| 3.2494        | 13.0  | 1118 | 2.7410          | 0.9776 | 0.7792 |
| 4.1417        | 14.0  | 1204 | 2.7921          | 0.9781 | 0.8052 |
| 4.1417        | 15.0  | 1290 | 2.7801          | 0.9720 | 0.7893 |
| 3.5813        | 16.0  | 1376 | 2.7245          | 0.9735 | 0.7797 |
| 3.7739        | 17.0  | 1462 | 2.7206          | 0.9633 | 0.7592 |
| 3.2666        | 18.0  | 1548 | 2.6764          | 0.9786 | 0.7518 |
| 3.5191        | 19.0  | 1634 | 2.6704          | 0.9771 | 0.7560 |
| 4.0333        | 20.0  | 1720 | 2.6269          | 0.9757 | 0.7216 |
| 3.155         | 21.0  | 1806 | 2.6349          | 0.9710 | 0.7388 |
| 3.155         | 22.0  | 1892 | 2.7308          | 0.9557 | 0.7501 |
| 3.4096        | 23.0  | 1978 | 2.5728          | 0.9727 | 0.7167 |
| 3.6189        | 24.0  | 2064 | 2.6209          | 0.9706 | 0.7134 |
| 3.1681        | 25.0  | 2150 | 2.5653          | 0.9662 | 0.7091 |
| 2.851         | 26.0  | 2236 | 2.5492          | 0.9601 | 0.7133 |
| 3.0625        | 27.0  | 2322 | 2.4696          | 0.9584 | 0.7059 |
| 2.6773        | 28.0  | 2408 | 2.4480          | 0.9708 | 0.6835 |
| 2.6773        | 29.0  | 2494 | 2.4551          | 0.9676 | 0.6831 |
| 2.6704        | 30.0  | 2580 | 2.3923          | 0.9615 | 0.6865 |
| 2.9334        | 31.0  | 2666 | 2.3834          | 0.9620 | 0.6748 |
| 2.8201        | 32.0  | 2752 | 2.3488          | 0.9615 | 0.6599 |
| 2.4969        | 33.0  | 2838 | 2.2633          | 0.9637 | 0.6578 |
| 2.5507        | 34.0  | 2924 | 2.2478          | 0.9744 | 0.6386 |
| 2.4824        | 35.0  | 3010 | 2.1524          | 0.9589 | 0.6350 |
| 2.4824        | 36.0  | 3096 | 2.1081          | 0.9523 | 0.6110 |
| 2.3294        | 37.0  | 3182 | 2.0454          | 0.9486 | 0.6230 |
| 2.2776        | 38.0  | 3268 | 1.9534          | 0.9435 | 0.5944 |
| 2.2266        | 39.0  | 3354 | 1.8659          | 0.9389 | 0.5765 |
| 2.2176        | 40.0  | 3440 | 1.8386          | 0.9277 | 0.5618 |
| 2.1509        | 41.0  | 3526 | 1.7009          | 0.9031 | 0.5146 |
| 2.0032        | 42.0  | 3612 | 1.5778          | 0.8936 | 0.5060 |
| 2.0032        | 43.0  | 3698 | 1.4811          | 0.8825 | 0.4663 |
| 1.8864        | 44.0  | 3784 | 1.2900          | 0.8576 | 0.4236 |
| 1.8023        | 45.0  | 3870 | 1.1809          | 0.7851 | 0.3400 |
| 1.7414        | 46.0  | 3956 | 1.0532          | 0.7802 | 0.3238 |
| 1.5595        | 47.0  | 4042 | 0.9481          | 0.7206 | 0.2759 |
| 1.4958        | 48.0  | 4128 | 0.8725          | 0.6960 | 0.2557 |
| 1.3644        | 49.0  | 4214 | 0.8044          | 0.6486 | 0.2255 |
| 1.4496        | 50.0  | 4300 | 0.6878          | 0.6074 | 0.1988 |
| 1.4496        | 51.0  | 4386 | 0.6003          | 0.5330 | 0.1622 |
| 1.0768        | 52.0  | 4472 | 0.5278          | 0.4609 | 0.1385 |
| 0.9745        | 53.0  | 4558 | 0.4708          | 0.3923 | 0.1158 |
| 0.8776        | 54.0  | 4644 | 0.4379          | 0.3558 | 0.1038 |
| 0.8135        | 55.0  | 4730 | 0.4097          | 0.3234 | 0.0945 |
| 0.7573        | 56.0  | 4816 | 0.3926          | 0.3088 | 0.0874 |
| 0.6982        | 57.0  | 4902 | 0.3704          | 0.2801 | 0.0801 |
| 0.6982        | 58.0  | 4988 | 0.3488          | 0.2587 | 0.0748 |
| 0.6478        | 59.0  | 5074 | 0.3264          | 0.2541 | 0.0710 |
| 0.6391        | 60.0  | 5160 | 0.3236          | 0.2314 | 0.0664 |
| 0.5856        | 61.0  | 5246 | 0.3106          | 0.2283 | 0.0644 |
| 0.5626        | 62.0  | 5332 | 0.3044          | 0.2176 | 0.0621 |
| 0.5698        | 63.0  | 5418 | 0.2993          | 0.2127 | 0.0601 |
| 0.5238        | 64.0  | 5504 | 0.2926          | 0.2039 | 0.0585 |
| 0.5238        | 65.0  | 5590 | 0.2852          | 0.2047 | 0.0577 |
| 0.4932        | 66.0  | 5676 | 0.2698          | 0.1932 | 0.0558 |
| 0.446         | 67.0  | 5762 | 0.2602          | 0.1932 | 0.0541 |
| 0.464         | 68.0  | 5848 | 0.2590          | 0.1852 | 0.0531 |
| 0.4482        | 69.0  | 5934 | 0.2508          | 0.1813 | 0.0520 |
| 0.4378        | 70.0  | 6020 | 0.2578          | 0.1691 | 0.0500 |
| 0.4682        | 71.0  | 6106 | 0.2496          | 0.1757 | 0.0505 |
| 0.4682        | 72.0  | 6192 | 0.2445          | 0.1713 | 0.0492 |
| 0.4296        | 73.0  | 6278 | 0.2445          | 0.1640 | 0.0483 |
| 0.4032        | 74.0  | 6364 | 0.2406          | 0.1640 | 0.0485 |
| 0.4357        | 75.0  | 6450 | 0.2398          | 0.1643 | 0.0484 |
| 0.4126        | 76.0  | 6536 | 0.2398          | 0.1611 | 0.0480 |
| 0.4006        | 77.0  | 6622 | 0.2343          | 0.1572 | 0.0468 |
| 0.3973        | 78.0  | 6708 | 0.2310          | 0.1531 | 0.0464 |
| 0.3973        | 79.0  | 6794 | 0.2368          | 0.1521 | 0.0459 |
| 0.3795        | 80.0  | 6880 | 0.2318          | 0.1523 | 0.0457 |
| 0.3926        | 81.0  | 6966 | 0.2287          | 0.1509 | 0.0455 |
| 0.3836        | 82.0  | 7052 | 0.2277          | 0.1519 | 0.0456 |
| 0.3746        | 83.0  | 7138 | 0.2245          | 0.1497 | 0.0445 |
| 0.3499        | 84.0  | 7224 | 0.2234          | 0.1514 | 0.0445 |
| 0.3572        | 85.0  | 7310 | 0.2234          | 0.1460 | 0.0444 |
| 0.3572        | 86.0  | 7396 | 0.2207          | 0.1470 | 0.0442 |
| 0.3358        | 87.0  | 7482 | 0.2186          | 0.1431 | 0.0441 |
| 0.3686        | 88.0  | 7568 | 0.2199          | 0.1487 | 0.0444 |
| 0.3572        | 89.0  | 7654 | 0.2194          | 0.1441 | 0.0442 |
| 0.3535        | 90.0  | 7740 | 0.2191          | 0.1453 | 0.0443 |
| 0.334         | 91.0  | 7826 | 0.2181          | 0.1443 | 0.0441 |
| 0.3153        | 92.0  | 7912 | 0.2177          | 0.1436 | 0.0438 |
| 0.3153        | 93.0  | 7998 | 0.2174          | 0.1412 | 0.0434 |
| 0.33          | 94.0  | 8084 | 0.2182          | 0.1455 | 0.0436 |
| 0.3167        | 95.0  | 8170 | 0.2181          | 0.1429 | 0.0432 |
| 0.3217        | 96.0  | 8256 | 0.2174          | 0.1429 | 0.0430 |
| 0.31          | 97.0  | 8342 | 0.2180          | 0.1394 | 0.0428 |
| 0.3307        | 98.0  | 8428 | 0.2179          | 0.1424 | 0.0431 |
| 0.3392        | 99.0  | 8514 | 0.2182          | 0.1412 | 0.0429 |
| 0.3468        | 100.0 | 8600 | 0.2177          | 0.1399 | 0.0430 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+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-05", "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-05
==================================================


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: 0.2174
* Wer: 0.1429
* Cer: 0.0430


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 2.0.1+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 2.0.1+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 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3