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-05
  results: []
---

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# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-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: 0.1042
- Wer: 0.0718
- Cer: 0.0214

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 28.8714       | 1.0   | 67   | 3.3571          | 1.0    | 1.0    |
| 7.5799        | 2.0   | 134  | 2.9876          | 1.0    | 1.0    |
| 3.0284        | 3.0   | 201  | 2.9114          | 1.0    | 1.0    |
| 3.0284        | 4.0   | 268  | 2.8889          | 1.0    | 1.0    |
| 2.9172        | 5.0   | 335  | 2.8515          | 1.0    | 1.0    |
| 2.8101        | 6.0   | 402  | 2.1557          | 1.0    | 0.6878 |
| 2.8101        | 7.0   | 469  | 0.7046          | 0.3468 | 0.0850 |
| 1.5251        | 8.0   | 536  | 0.4276          | 0.1963 | 0.0517 |
| 0.7791        | 9.0   | 603  | 0.3256          | 0.1723 | 0.0455 |
| 0.7791        | 10.0  | 670  | 0.2743          | 0.1416 | 0.0388 |
| 0.5599        | 11.0  | 737  | 0.2362          | 0.1387 | 0.0378 |
| 0.4678        | 12.0  | 804  | 0.2119          | 0.1265 | 0.0352 |
| 0.4678        | 13.0  | 871  | 0.1984          | 0.1179 | 0.0339 |
| 0.4302        | 14.0  | 938  | 0.1834          | 0.1235 | 0.0332 |
| 0.3794        | 15.0  | 1005 | 0.1760          | 0.1133 | 0.0310 |
| 0.3794        | 16.0  | 1072 | 0.1763          | 0.1080 | 0.0309 |
| 0.3234        | 17.0  | 1139 | 0.1583          | 0.1018 | 0.0294 |
| 0.3144        | 18.0  | 1206 | 0.1570          | 0.0932 | 0.0275 |
| 0.3144        | 19.0  | 1273 | 0.1421          | 0.0912 | 0.0263 |
| 0.2824        | 20.0  | 1340 | 0.1448          | 0.0886 | 0.0263 |
| 0.2503        | 21.0  | 1407 | 0.1371          | 0.0916 | 0.0260 |
| 0.2503        | 22.0  | 1474 | 0.1387          | 0.0860 | 0.0253 |
| 0.2547        | 23.0  | 1541 | 0.1301          | 0.0863 | 0.0242 |
| 0.2397        | 24.0  | 1608 | 0.1272          | 0.0823 | 0.0239 |
| 0.2397        | 25.0  | 1675 | 0.1368          | 0.0827 | 0.0250 |
| 0.2402        | 26.0  | 1742 | 0.1303          | 0.0807 | 0.0243 |
| 0.2581        | 27.0  | 1809 | 0.1248          | 0.0777 | 0.0239 |
| 0.2581        | 28.0  | 1876 | 0.1242          | 0.0758 | 0.0225 |
| 0.2334        | 29.0  | 1943 | 0.1231          | 0.0774 | 0.0228 |
| 0.2087        | 30.0  | 2010 | 0.1226          | 0.0754 | 0.0224 |
| 0.2087        | 31.0  | 2077 | 0.1227          | 0.0774 | 0.0230 |
| 0.2175        | 32.0  | 2144 | 0.1270          | 0.0767 | 0.0231 |
| 0.1973        | 33.0  | 2211 | 0.1258          | 0.0754 | 0.0230 |
| 0.1973        | 34.0  | 2278 | 0.1186          | 0.0754 | 0.0223 |
| 0.1787        | 35.0  | 2345 | 0.1234          | 0.0735 | 0.0217 |
| 0.1958        | 36.0  | 2412 | 0.1199          | 0.0741 | 0.0222 |
| 0.1958        | 37.0  | 2479 | 0.1177          | 0.0754 | 0.0222 |
| 0.1773        | 38.0  | 2546 | 0.1138          | 0.0751 | 0.0225 |
| 0.2047        | 39.0  | 2613 | 0.1164          | 0.0751 | 0.0224 |
| 0.2047        | 40.0  | 2680 | 0.1155          | 0.0751 | 0.0227 |
| 0.1727        | 41.0  | 2747 | 0.1109          | 0.0728 | 0.0213 |
| 0.1708        | 42.0  | 2814 | 0.1132          | 0.0702 | 0.0213 |
| 0.1708        | 43.0  | 2881 | 0.1110          | 0.0728 | 0.0217 |
| 0.1814        | 44.0  | 2948 | 0.1094          | 0.0711 | 0.0215 |
| 0.159         | 45.0  | 3015 | 0.1091          | 0.0702 | 0.0211 |
| 0.159         | 46.0  | 3082 | 0.1065          | 0.0702 | 0.0208 |
| 0.163         | 47.0  | 3149 | 0.1110          | 0.0708 | 0.0210 |
| 0.1565        | 48.0  | 3216 | 0.1121          | 0.0725 | 0.0215 |
| 0.1565        | 49.0  | 3283 | 0.1096          | 0.0715 | 0.0215 |
| 0.1571        | 50.0  | 3350 | 0.1083          | 0.0718 | 0.0210 |
| 0.165         | 51.0  | 3417 | 0.1056          | 0.0711 | 0.0210 |
| 0.165         | 52.0  | 3484 | 0.1042          | 0.0718 | 0.0214 |
| 0.1525        | 53.0  | 3551 | 0.1067          | 0.0698 | 0.0209 |
| 0.1365        | 54.0  | 3618 | 0.1084          | 0.0715 | 0.0208 |
| 0.1365        | 55.0  | 3685 | 0.1086          | 0.0735 | 0.0215 |
| 0.1434        | 56.0  | 3752 | 0.1073          | 0.0711 | 0.0208 |
| 0.1408        | 57.0  | 3819 | 0.1062          | 0.0705 | 0.0209 |
| 0.1408        | 58.0  | 3886 | 0.1066          | 0.0708 | 0.0205 |
| 0.1364        | 59.0  | 3953 | 0.1074          | 0.0702 | 0.0207 |
| 0.1507        | 60.0  | 4020 | 0.1049          | 0.0725 | 0.0207 |
| 0.1507        | 61.0  | 4087 | 0.1086          | 0.0715 | 0.0211 |
| 0.1532        | 62.0  | 4154 | 0.1083          | 0.0738 | 0.0210 |
| 0.1255        | 63.0  | 4221 | 0.1058          | 0.0721 | 0.0207 |
| 0.1255        | 64.0  | 4288 | 0.1087          | 0.0708 | 0.0202 |
| 0.1534        | 65.0  | 4355 | 0.1073          | 0.0738 | 0.0208 |
| 0.1316        | 66.0  | 4422 | 0.1061          | 0.0731 | 0.0210 |
| 0.1316        | 67.0  | 4489 | 0.1082          | 0.0731 | 0.0208 |
| 0.1365        | 68.0  | 4556 | 0.1100          | 0.0751 | 0.0213 |
| 0.1324        | 69.0  | 4623 | 0.1104          | 0.0708 | 0.0206 |
| 0.1324        | 70.0  | 4690 | 0.1073          | 0.0721 | 0.0206 |
| 0.1299        | 71.0  | 4757 | 0.1104          | 0.0711 | 0.0211 |
| 0.125         | 72.0  | 4824 | 0.1078          | 0.0718 | 0.0212 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.1+cu121
- Datasets 2.17.1
- Tokenizers 0.13.3
