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---
language:
- cs
license: apache-2.0
tags:
- automatic-speech-recognition
- cs
- generated_from_trainer
- hf-asr-leaderboard
- model_for_talk
- mozilla-foundation/common_voice_8_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: sammy786/wav2vec2-xlsr-czech
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: cs
metrics:
- name: Test WER
type: wer
value: 11.22
- name: Test CER
type: cer
value: 2.52
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: cs
metrics:
- name: Test WER
type: wer
value: 97.02
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: cs
metrics:
- name: Test WER
type: wer
value: 69.7
---
# sammy786/wav2vec2-xlsr-czech
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - cs dataset.
It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
- Loss: 7.26
- Wer: 19.32
## Model description
"facebook/wav2vec2-xls-r-1b" was finetuned.
## Intended uses & limitations
More information needed
## Training and evaluation data
Training data -
Common voice Finnish train.tsv, dev.tsv, invalidated.tsv and other.tsv
## Training procedure
For creating the train dataset, all possible datasets were appended and 90-10 split was used.
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.000045637994662983496
- train_batch_size: 8
- eval_batch_size: 16
- seed: 13
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 500
- num_epochs: 7
- mixed_precision_training: Native AMP
### Training results
| Step | Training Loss | Validation Loss | Wer |
|:----:|:-------------:|:---------------:|:--------:|
| 200 | 6.654600 | 3.329486 | 1.000000 |
| 400 | 1.700600 | 0.317266 | 0.409446 |
| 600 | 0.767400 | 0.211371 | 0.313981 |
| 800 | 0.718600 | 0.167771 | 0.280676 |
| 1000 | 0.661700 | 0.142229 | 0.258938 |
| 1200 | 0.594400 | 0.137321 | 0.256275 |
| 1400 | 0.583900 | 0.132922 | 0.248418 |
| 1600 | 0.565100 | 0.117214 | 0.238640 |
| 1800 | 0.369600 | 0.116954 | 0.238291 |
| 2000 | 0.292800 | 0.109973 | 0.227509 |
| 2200 | 0.255400 | 0.104955 | 0.228120 |
| 2400 | 0.266800 | 0.097268 | 0.220525 |
| 2600 | 0.232700 | 0.096055 | 0.213584 |
| 2800 | 0.213700 | 0.097770 | 0.218866 |
| 3000 | 0.209900 | 0.091633 | 0.210485 |
| 3200 | 0.196800 | 0.090342 | 0.208739 |
| 3400 | 0.200500 | 0.082326 | 0.204767 |
| 3600 | 0.176800 | 0.085491 | 0.204068 |
| 3800 | 0.170000 | 0.081289 | 0.201231 |
| 4000 | 0.166200 | 0.080762 | 0.200227 |
| 4200 | 0.161700 | 0.076671 | 0.198001 |
| 4400 | 0.147000 | 0.077383 | 0.196997 |
| 4600 | 0.141900 | 0.076057 | 0.195862 |
| 4800 | 0.144800 | 0.074612 | 0.195120 |
| 5000 | 0.138900 | 0.073138 | 0.193985 |
| 5200 | 0.143900 | 0.072802 | 0.192894 |
| 5400 | 0.131100 | 0.072764 | 0.193723 |
| 5600 | 0.137000 | 0.072697 | 0.193679 |
| 5800 | 0.133300 | 0.072651 | 0.193286 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.10.3
#### Evaluation Commands
1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`
```bash
python eval.py --model_id sammy786/wav2vec2-xlsr-czech --dataset mozilla-foundation/common_voice_8_0 --config cs --split test
``` |