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---
license: apache-2.0
language:
- ru
tags:
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-xls-r-300m-Russian-small
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice ru
type: common_voice
args: ru
metrics:
- name: Test WER
type: wer
value: 48.38
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: ru
metrics:
- name: Test WER
type: wer
value: 58.25
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: ru
metrics:
- name: Test WER
type: wer
value: 56.83
---
<!-- 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-xls-r-300m-Russian-small
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3514
- Wer: 0.4838
## 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: 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.512 | 1.32 | 400 | 3.2207 | 1.0 |
| 3.1562 | 2.65 | 800 | 3.0166 | 1.0 |
| 1.5211 | 3.97 | 1200 | 0.7134 | 0.8275 |
| 0.6724 | 5.3 | 1600 | 0.4713 | 0.6402 |
| 0.4693 | 6.62 | 2000 | 0.3904 | 0.5668 |
| 0.3693 | 7.95 | 2400 | 0.3609 | 0.5121 |
| 0.3004 | 9.27 | 2800 | 0.3514 | 0.4838 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3