transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-06
  results: []
---

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# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-06

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: 0.1245
- Wer: 0.0826
- Cer: 0.0242

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 25.0528       | 1.0   | 67   | 3.3339          | 1.0    | 1.0    |
| 7.3126        | 2.0   | 134  | 2.9659          | 1.0    | 1.0    |
| 3.0007        | 3.0   | 201  | 2.9192          | 1.0    | 1.0    |
| 3.0007        | 4.0   | 268  | 2.8943          | 1.0    | 1.0    |
| 2.9153        | 5.0   | 335  | 2.8720          | 1.0    | 1.0    |
| 2.8426        | 6.0   | 402  | 2.4681          | 0.9980 | 0.9974 |
| 2.8426        | 7.0   | 469  | 0.8337          | 0.4926 | 0.1146 |
| 1.7153        | 8.0   | 536  | 0.4488          | 0.2116 | 0.0571 |
| 0.791         | 9.0   | 603  | 0.3345          | 0.1825 | 0.0507 |
| 0.791         | 10.0  | 670  | 0.2795          | 0.1584 | 0.0451 |
| 0.5835        | 11.0  | 737  | 0.2457          | 0.1469 | 0.0422 |
| 0.4836        | 12.0  | 804  | 0.2251          | 0.1398 | 0.0407 |
| 0.4836        | 13.0  | 871  | 0.2120          | 0.1303 | 0.0379 |
| 0.4026        | 14.0  | 938  | 0.1947          | 0.1141 | 0.0348 |
| 0.3347        | 15.0  | 1005 | 0.1764          | 0.1090 | 0.0324 |
| 0.3347        | 16.0  | 1072 | 0.1703          | 0.1070 | 0.0320 |
| 0.3405        | 17.0  | 1139 | 0.1647          | 0.1019 | 0.0311 |
| 0.3036        | 18.0  | 1206 | 0.1571          | 0.0911 | 0.0286 |
| 0.3036        | 19.0  | 1273 | 0.1541          | 0.0955 | 0.0292 |
| 0.2859        | 20.0  | 1340 | 0.1528          | 0.0961 | 0.0300 |
| 0.2499        | 21.0  | 1407 | 0.1514          | 0.0907 | 0.0288 |
| 0.2499        | 22.0  | 1474 | 0.1502          | 0.0884 | 0.0284 |
| 0.2709        | 23.0  | 1541 | 0.1435          | 0.0843 | 0.0269 |
| 0.2446        | 24.0  | 1608 | 0.1405          | 0.0850 | 0.0267 |
| 0.2446        | 25.0  | 1675 | 0.1379          | 0.0846 | 0.0272 |
| 0.2131        | 26.0  | 1742 | 0.1375          | 0.0843 | 0.0263 |
| 0.2333        | 27.0  | 1809 | 0.1374          | 0.0856 | 0.0275 |
| 0.2333        | 28.0  | 1876 | 0.1408          | 0.0856 | 0.0274 |
| 0.216         | 29.0  | 1943 | 0.1341          | 0.0809 | 0.0261 |
| 0.1948        | 30.0  | 2010 | 0.1344          | 0.0863 | 0.0266 |
| 0.1948        | 31.0  | 2077 | 0.1353          | 0.0833 | 0.0263 |
| 0.1957        | 32.0  | 2144 | 0.1296          | 0.0823 | 0.0255 |
| 0.2116        | 33.0  | 2211 | 0.1350          | 0.0826 | 0.0263 |
| 0.2116        | 34.0  | 2278 | 0.1344          | 0.0812 | 0.0259 |
| 0.1862        | 35.0  | 2345 | 0.1361          | 0.0819 | 0.0260 |
| 0.1819        | 36.0  | 2412 | 0.1349          | 0.0836 | 0.0264 |
| 0.1819        | 37.0  | 2479 | 0.1305          | 0.0836 | 0.0256 |
| 0.1622        | 38.0  | 2546 | 0.1284          | 0.0823 | 0.0258 |
| 0.1693        | 39.0  | 2613 | 0.1295          | 0.0853 | 0.0262 |
| 0.1693        | 40.0  | 2680 | 0.1321          | 0.0833 | 0.0261 |
| 0.1865        | 41.0  | 2747 | 0.1278          | 0.0812 | 0.0255 |
| 0.1646        | 42.0  | 2814 | 0.1307          | 0.0816 | 0.0258 |
| 0.1646        | 43.0  | 2881 | 0.1284          | 0.0823 | 0.0262 |
| 0.1526        | 44.0  | 2948 | 0.1312          | 0.0833 | 0.0256 |
| 0.1708        | 45.0  | 3015 | 0.1273          | 0.0819 | 0.0247 |
| 0.1708        | 46.0  | 3082 | 0.1266          | 0.0782 | 0.0240 |
| 0.1582        | 47.0  | 3149 | 0.1260          | 0.0796 | 0.0245 |
| 0.1448        | 48.0  | 3216 | 0.1252          | 0.0785 | 0.0240 |
| 0.1448        | 49.0  | 3283 | 0.1259          | 0.0789 | 0.0233 |
| 0.1425        | 50.0  | 3350 | 0.1262          | 0.0833 | 0.0247 |
| 0.1502        | 51.0  | 3417 | 0.1264          | 0.0806 | 0.0243 |
| 0.1502        | 52.0  | 3484 | 0.1245          | 0.0826 | 0.0242 |
| 0.1337        | 53.0  | 3551 | 0.1299          | 0.0809 | 0.0249 |
| 0.1523        | 54.0  | 3618 | 0.1303          | 0.0816 | 0.0249 |
| 0.1523        | 55.0  | 3685 | 0.1295          | 0.0833 | 0.0249 |
| 0.1365        | 56.0  | 3752 | 0.1277          | 0.0833 | 0.0255 |
| 0.1435        | 57.0  | 3819 | 0.1286          | 0.0829 | 0.0249 |
| 0.1435        | 58.0  | 3886 | 0.1264          | 0.0833 | 0.0250 |
| 0.1319        | 59.0  | 3953 | 0.1309          | 0.0819 | 0.0252 |
| 0.1473        | 60.0  | 4020 | 0.1272          | 0.0799 | 0.0241 |
| 0.1473        | 61.0  | 4087 | 0.1260          | 0.0806 | 0.0245 |
| 0.1419        | 62.0  | 4154 | 0.1264          | 0.0796 | 0.0241 |
| 0.1371        | 63.0  | 4221 | 0.1293          | 0.0789 | 0.0251 |
| 0.1371        | 64.0  | 4288 | 0.1276          | 0.0768 | 0.0244 |
| 0.1301        | 65.0  | 4355 | 0.1262          | 0.0789 | 0.0246 |
| 0.1341        | 66.0  | 4422 | 0.1280          | 0.0823 | 0.0256 |
| 0.1341        | 67.0  | 4489 | 0.1300          | 0.0826 | 0.0254 |
| 0.1283        | 68.0  | 4556 | 0.1280          | 0.0768 | 0.0241 |
| 0.1241        | 69.0  | 4623 | 0.1289          | 0.0768 | 0.0238 |
| 0.1241        | 70.0  | 4690 | 0.1305          | 0.0782 | 0.0245 |
| 0.1326        | 71.0  | 4757 | 0.1295          | 0.0782 | 0.0247 |
| 0.1244        | 72.0  | 4824 | 0.1287          | 0.0796 | 0.0250 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.2.1+cu121
- Datasets 2.17.0
- Tokenizers 0.13.3
