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: xls-r-300m-model-C
  results: []
---

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# xls-r-300m-model-C

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3299
- Wer: 0.4263
- Cer: 0.2096

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 60
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 26.9708       | 1.0   | 47   | 11.3572         | 1.0    | 1.0    |
| 8.8174        | 2.0   | 94   | 4.0787          | 1.0    | 1.0    |
| 3.6382        | 3.0   | 141  | 3.1642          | 1.0    | 1.0    |
| 3.1662        | 4.0   | 188  | 3.1463          | 1.0    | 1.0    |
| 3.1612        | 5.0   | 235  | 3.1479          | 1.0    | 1.0    |
| 3.1256        | 6.0   | 282  | 3.0059          | 1.0    | 1.0    |
| 2.9892        | 7.0   | 329  | 3.1620          | 1.0    | 1.0    |
| 2.8792        | 8.0   | 376  | 2.7184          | 1.0    | 1.0    |
| 2.7882        | 9.0   | 423  | 2.6526          | 1.0    | 0.8751 |
| 2.6556        | 10.0  | 470  | 2.5504          | 1.0    | 0.8299 |
| 2.5528        | 11.0  | 517  | 2.4123          | 1.0    | 0.8659 |
| 2.416         | 12.0  | 564  | 2.2641          | 1.0    | 0.7833 |
| 2.2796        | 13.0  | 611  | 2.1311          | 1.0    | 0.7459 |
| 2.1592        | 14.0  | 658  | 1.9811          | 1.0    | 0.7234 |
| 2.1128        | 15.0  | 705  | 2.0185          | 1.0    | 0.7622 |
| 2.0422        | 16.0  | 752  | 1.9119          | 1.0    | 0.7565 |
| 2.0077        | 17.0  | 799  | 1.8053          | 1.0    | 0.7530 |
| 1.9033        | 18.0  | 846  | 1.7593          | 1.0031 | 0.7198 |
| 1.8717        | 19.0  | 893  | 1.6809          | 0.9937 | 0.6443 |
| 1.7898        | 20.0  | 940  | 1.6353          | 0.9624 | 0.6683 |
| 1.7377        | 21.0  | 987  | 1.5580          | 1.0094 | 0.7114 |
| 1.6328        | 22.0  | 1034 | 1.3971          | 0.9718 | 0.6069 |
| 1.596         | 23.0  | 1081 | 1.3844          | 1.0784 | 0.6013 |
| 1.5422        | 24.0  | 1128 | 1.2812          | 0.9028 | 0.4989 |
| 1.3451        | 25.0  | 1175 | 1.2919          | 0.9279 | 0.5695 |
| 1.246         | 26.0  | 1222 | 1.1572          | 0.8871 | 0.5039 |
| 1.237         | 27.0  | 1269 | 1.2349          | 0.9028 | 0.5349 |
| 1.1147        | 28.0  | 1316 | 0.9799          | 0.8401 | 0.4771 |
| 0.9404        | 29.0  | 1363 | 0.9032          | 0.7743 | 0.4390 |
| 0.9353        | 30.0  | 1410 | 0.7554          | 0.8088 | 0.4700 |
| 0.8467        | 31.0  | 1457 | 0.8404          | 0.7586 | 0.4107 |
| 0.8398        | 32.0  | 1504 | 0.7486          | 0.7618 | 0.4234 |
| 0.7437        | 33.0  | 1551 | 0.6802          | 0.6897 | 0.3529 |
| 0.606         | 34.0  | 1598 | 0.7355          | 0.6959 | 0.3677 |
| 0.6243        | 35.0  | 1645 | 0.7037          | 0.6708 | 0.3331 |
| 0.5461        | 36.0  | 1692 | 0.7073          | 0.6207 | 0.2886 |
| 0.5483        | 37.0  | 1739 | 0.6538          | 0.6301 | 0.3140 |
| 0.5257        | 38.0  | 1786 | 0.5984          | 0.5674 | 0.3296 |
| 0.4714        | 39.0  | 1833 | 0.5388          | 0.5956 | 0.3162 |
| 0.4328        | 40.0  | 1880 | 0.4635          | 0.5737 | 0.3183 |
| 0.4192        | 41.0  | 1927 | 0.6038          | 0.5768 | 0.3126 |
| 0.3659        | 42.0  | 1974 | 0.5909          | 0.5705 | 0.2908 |
| 0.3587        | 43.0  | 2021 | 0.3662          | 0.4639 | 0.2385 |
| 0.3755        | 44.0  | 2068 | 0.4218          | 0.4859 | 0.2590 |
| 0.2926        | 45.0  | 2115 | 0.3366          | 0.4890 | 0.2449 |
| 0.3428        | 46.0  | 2162 | 0.4311          | 0.5016 | 0.2745 |
| 0.301         | 47.0  | 2209 | 0.3943          | 0.4828 | 0.2604 |
| 0.262         | 48.0  | 2256 | 0.4424          | 0.4796 | 0.2414 |
| 0.308         | 49.0  | 2303 | 0.3152          | 0.4639 | 0.2329 |
| 0.2434        | 50.0  | 2350 | 0.4463          | 0.4671 | 0.2392 |
| 0.1922        | 51.0  | 2397 | 0.4145          | 0.4483 | 0.2308 |
| 0.1913        | 52.0  | 2444 | 0.3989          | 0.4295 | 0.2082 |
| 0.2115        | 53.0  | 2491 | 0.3491          | 0.4545 | 0.2124 |
| 0.215         | 54.0  | 2538 | 0.4084          | 0.4451 | 0.2329 |
| 0.1854        | 55.0  | 2585 | 0.4447          | 0.4451 | 0.2399 |
| 0.1556        | 56.0  | 2632 | 0.4437          | 0.4702 | 0.2336 |
| 0.1564        | 57.0  | 2679 | 0.4627          | 0.4389 | 0.2188 |
| 0.1502        | 58.0  | 2726 | 0.4350          | 0.4295 | 0.2145 |
| 0.1571        | 59.0  | 2773 | 0.3444          | 0.4295 | 0.2096 |
| 0.1319        | 60.0  | 2820 | 0.3299          | 0.4263 | 0.2096 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.13.3
