metadata
language:
- ka
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- ka
- robust-speech-event
- model_for_talk
- hf-asr-leaderboard
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: ka
metrics:
- name: Test WER
type: wer
value: 23.9
- name: Test CER
type: cer
value: 3.59
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: ka
metrics:
- name: Test WER
type: wer
value: 75.07
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: ka
metrics:
- name: Test WER
type: wer
value: 74.41
sammy786/wav2vec2-xlsr-georgian
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - ka dataset. It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
- Loss: 10.54
- Wer: 27.53
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 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: 30
- mixed_precision_training: Native AMP
Training results
Step | Training Loss | Validation Loss | Wer |
---|---|---|---|
200 | 4.152100 | 0.823672 | 0.967814 |
400 | 0.889500 | 0.196740 | 0.444792 |
600 | 0.493700 | 0.155659 | 0.366115 |
800 | 0.328000 | 0.138066 | 0.358069 |
1000 | 0.260600 | 0.119236 | 0.324989 |
1200 | 0.217200 | 0.114050 | 0.313366 |
1400 | 0.188800 | 0.112600 | 0.302190 |
1600 | 0.166900 | 0.111154 | 0.295485 |
1800 | 0.155500 | 0.109963 | 0.286544 |
2000 | 0.140400 | 0.107587 | 0.277604 |
2200 | 0.142600 | 0.105662 | 0.277157 |
2400 | 0.135400 | 0.105414 | 0.275369 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.10.3
Evaluation Commands
- To evaluate on
mozilla-foundation/common_voice_8_0
with splittest
python eval.py --model_id sammy786/wav2vec2-xlsr-georgian --dataset mozilla-foundation/common_voice_8_0 --config ka --split test