---
license: apache-2.0
base_model: jonatasgrosman/wav2vec2-large-xlsr-53-russian
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-ru-snr10-commonvoice_train3000_val200
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: ru
      split: test[0:200]
      args: ru
    metrics:
    - name: Wer
      type: wer
      value: 0.5075114304376225
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-large-xlsr-53-ru-snr10-commonvoice_train3000_val200

This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-russian](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-russian) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3736
- Wer: 0.5075
- Cer: 0.2395

## 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: 0.0001
- train_batch_size: 16
- 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_steps: 100
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.9298        | 0.96  | 180  | 1.0829          | 0.6153 | 0.2984 |
| 0.6185        | 1.91  | 360  | 1.1071          | 0.5924 | 0.2899 |
| 0.5395        | 2.87  | 540  | 1.0219          | 0.5558 | 0.2604 |
| 0.464         | 3.83  | 720  | 1.0042          | 0.5363 | 0.2564 |
| 0.4346        | 4.79  | 900  | 0.9817          | 0.5323 | 0.2403 |
| 0.4025        | 5.74  | 1080 | 1.0918          | 0.5558 | 0.2549 |
| 0.358         | 6.7   | 1260 | 1.0987          | 0.5336 | 0.2437 |
| 0.3466        | 7.66  | 1440 | 1.0802          | 0.5349 | 0.2437 |
| 0.3215        | 8.62  | 1620 | 1.1377          | 0.5467 | 0.2588 |
| 0.3247        | 9.57  | 1800 | 1.0324          | 0.5153 | 0.2350 |
| 0.287         | 10.53 | 1980 | 1.1466          | 0.5565 | 0.2603 |
| 0.2716        | 11.49 | 2160 | 1.2634          | 0.5532 | 0.2536 |
| 0.2555        | 12.45 | 2340 | 1.1859          | 0.5160 | 0.2318 |
| 0.2454        | 13.4  | 2520 | 1.1147          | 0.5186 | 0.2278 |
| 0.2299        | 14.36 | 2700 | 1.1287          | 0.5167 | 0.2282 |
| 0.2269        | 15.32 | 2880 | 1.2123          | 0.5042 | 0.2275 |
| 0.2132        | 16.28 | 3060 | 1.1219          | 0.5082 | 0.2297 |
| 0.1965        | 17.23 | 3240 | 1.2263          | 0.5167 | 0.2345 |
| 0.1943        | 18.19 | 3420 | 1.2679          | 0.5284 | 0.2353 |
| 0.1867        | 19.15 | 3600 | 1.2097          | 0.5186 | 0.2422 |
| 0.1851        | 20.11 | 3780 | 1.3118          | 0.5147 | 0.2330 |
| 0.1709        | 21.06 | 3960 | 1.1834          | 0.5193 | 0.2374 |
| 0.1757        | 22.02 | 4140 | 1.3010          | 0.5036 | 0.2272 |
| 0.1661        | 22.98 | 4320 | 1.2384          | 0.5075 | 0.2313 |
| 0.1607        | 23.94 | 4500 | 1.3642          | 0.5219 | 0.2421 |
| 0.1611        | 24.89 | 4680 | 1.3055          | 0.5108 | 0.2363 |
| 0.1567        | 25.85 | 4860 | 1.3666          | 0.5140 | 0.2383 |
| 0.1469        | 26.81 | 5040 | 1.3888          | 0.5101 | 0.2367 |
| 0.1432        | 27.77 | 5220 | 1.3478          | 0.5206 | 0.2333 |
| 0.1479        | 28.72 | 5400 | 1.3297          | 0.4918 | 0.2291 |
| 0.144         | 29.68 | 5580 | 1.3736          | 0.5075 | 0.2395 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0