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---
language:
- cv
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- cv
- robust-speech-event
- model_for_talk
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Chuvash
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: cv
metrics:
- name: Test WER
type: wer
value: 60.31
- name: Test CER
type: cer
value: 15.08
---
<!-- 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-xls-r-300m-chuvash
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - CV dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7651
- Wer: 0.6166
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.8032 | 8.77 | 500 | 0.8059 | 0.8352 |
| 1.2608 | 17.54 | 1000 | 0.5828 | 0.6769 |
| 1.1337 | 26.32 | 1500 | 0.6892 | 0.6908 |
| 1.0457 | 35.09 | 2000 | 0.7077 | 0.6781 |
| 0.97 | 43.86 | 2500 | 0.5993 | 0.6228 |
| 0.8767 | 52.63 | 3000 | 0.7213 | 0.6604 |
| 0.8223 | 61.4 | 3500 | 0.8161 | 0.6968 |
| 0.7441 | 70.18 | 4000 | 0.7057 | 0.6184 |
| 0.7011 | 78.95 | 4500 | 0.7027 | 0.6024 |
| 0.6542 | 87.72 | 5000 | 0.7092 | 0.5979 |
| 0.6081 | 96.49 | 5500 | 0.7917 | 0.6324 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
|