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-07
  results: []
---

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# wav2vec2-large-xlsr-mecita-coraa-portuguese-2-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: 0.1209
- Wer: 0.0903
- Cer: 0.0256

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 27.4046       | 1.0   | 67   | 3.3438          | 1.0    | 1.0    |
| 6.9713        | 2.0   | 134  | 2.9841          | 1.0    | 1.0    |
| 3.0045        | 3.0   | 201  | 2.9144          | 1.0    | 1.0    |
| 3.0045        | 4.0   | 268  | 2.8956          | 1.0    | 1.0    |
| 2.9124        | 5.0   | 335  | 2.7397          | 1.0    | 1.0    |
| 2.5598        | 6.0   | 402  | 1.2712          | 0.8962 | 0.2337 |
| 2.5598        | 7.0   | 469  | 0.5554          | 0.2947 | 0.0751 |
| 1.1631        | 8.0   | 536  | 0.3916          | 0.1968 | 0.0531 |
| 0.6927        | 9.0   | 603  | 0.3124          | 0.1737 | 0.0463 |
| 0.6927        | 10.0  | 670  | 0.2679          | 0.1672 | 0.0433 |
| 0.5782        | 11.0  | 737  | 0.2395          | 0.1537 | 0.0405 |
| 0.4523        | 12.0  | 804  | 0.2139          | 0.1365 | 0.0372 |
| 0.4523        | 13.0  | 871  | 0.2009          | 0.1275 | 0.0354 |
| 0.3903        | 14.0  | 938  | 0.1852          | 0.1138 | 0.0317 |
| 0.3522        | 15.0  | 1005 | 0.1734          | 0.1165 | 0.0319 |
| 0.3522        | 16.0  | 1072 | 0.1669          | 0.1089 | 0.0294 |
| 0.3397        | 17.0  | 1139 | 0.1607          | 0.1058 | 0.0296 |
| 0.2904        | 18.0  | 1206 | 0.1536          | 0.0969 | 0.0277 |
| 0.2904        | 19.0  | 1273 | 0.1503          | 0.0979 | 0.0277 |
| 0.2733        | 20.0  | 1340 | 0.1472          | 0.0938 | 0.0275 |
| 0.2698        | 21.0  | 1407 | 0.1417          | 0.0948 | 0.0273 |
| 0.2698        | 22.0  | 1474 | 0.1403          | 0.0903 | 0.0266 |
| 0.2439        | 23.0  | 1541 | 0.1368          | 0.0965 | 0.0262 |
| 0.2348        | 24.0  | 1608 | 0.1364          | 0.0927 | 0.0263 |
| 0.2348        | 25.0  | 1675 | 0.1333          | 0.0920 | 0.0263 |
| 0.2241        | 26.0  | 1742 | 0.1342          | 0.0924 | 0.0267 |
| 0.2174        | 27.0  | 1809 | 0.1336          | 0.0931 | 0.0266 |
| 0.2174        | 28.0  | 1876 | 0.1352          | 0.0910 | 0.0266 |
| 0.2325        | 29.0  | 1943 | 0.1315          | 0.0927 | 0.0260 |
| 0.1873        | 30.0  | 2010 | 0.1298          | 0.0924 | 0.0260 |
| 0.1873        | 31.0  | 2077 | 0.1255          | 0.0865 | 0.0248 |
| 0.1926        | 32.0  | 2144 | 0.1251          | 0.0876 | 0.0253 |
| 0.1934        | 33.0  | 2211 | 0.1274          | 0.0879 | 0.0253 |
| 0.1934        | 34.0  | 2278 | 0.1209          | 0.0903 | 0.0256 |
| 0.2157        | 35.0  | 2345 | 0.1233          | 0.0879 | 0.0253 |
| 0.1855        | 36.0  | 2412 | 0.1242          | 0.0900 | 0.0252 |
| 0.1855        | 37.0  | 2479 | 0.1210          | 0.0851 | 0.0240 |
| 0.1644        | 38.0  | 2546 | 0.1260          | 0.0841 | 0.0241 |
| 0.1666        | 39.0  | 2613 | 0.1243          | 0.0862 | 0.0242 |
| 0.1666        | 40.0  | 2680 | 0.1254          | 0.0855 | 0.0247 |
| 0.1883        | 41.0  | 2747 | 0.1233          | 0.0834 | 0.0246 |
| 0.175         | 42.0  | 2814 | 0.1253          | 0.0831 | 0.0242 |
| 0.175         | 43.0  | 2881 | 0.1239          | 0.0827 | 0.0241 |
| 0.1763        | 44.0  | 2948 | 0.1250          | 0.0838 | 0.0242 |
| 0.1615        | 45.0  | 3015 | 0.1226          | 0.0872 | 0.0245 |
| 0.1615        | 46.0  | 3082 | 0.1235          | 0.0879 | 0.0247 |
| 0.1544        | 47.0  | 3149 | 0.1227          | 0.0858 | 0.0246 |
| 0.1554        | 48.0  | 3216 | 0.1217          | 0.0862 | 0.0246 |
| 0.1554        | 49.0  | 3283 | 0.1247          | 0.0876 | 0.0248 |
| 0.1476        | 50.0  | 3350 | 0.1221          | 0.0855 | 0.0246 |
| 0.1649        | 51.0  | 3417 | 0.1237          | 0.0855 | 0.0238 |
| 0.1649        | 52.0  | 3484 | 0.1244          | 0.0841 | 0.0242 |
| 0.144         | 53.0  | 3551 | 0.1246          | 0.0858 | 0.0244 |
| 0.1434        | 54.0  | 3618 | 0.1241          | 0.0831 | 0.0235 |


### Framework versions

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