metadata
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- robust-speech-event
- et
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: xls-r-et-cv_8_0
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: et
metrics:
- name: Test WER
type: wer
value: 0.34180826781638346
- name: Test CER
type: cer
value: 0.07356192733576256
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8.0
type: mozilla-foundation/common_voice_8_0
args: et
metrics:
- name: Test WER
type: wer
value: 34.18
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: et
metrics:
- name: Test WER
type: wer
value: 45.53
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: et
metrics:
- name: Test WER
type: wer
value: 54.41
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - ET dataset. It achieves the following results on the evaluation set:
- Loss: 0.4623
- Wer: 0.3420
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: 72
- eval_batch_size: 72
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 144
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 100.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3082 | 12.5 | 500 | 0.3871 | 0.4907 |
| 0.1497 | 25.0 | 1000 | 0.4168 | 0.4278 |
| 0.1243 | 37.5 | 1500 | 0.4446 | 0.4220 |
| 0.0954 | 50.0 | 2000 | 0.4426 | 0.3946 |
| 0.0741 | 62.5 | 2500 | 0.4502 | 0.3800 |
| 0.0533 | 75.0 | 3000 | 0.4618 | 0.3653 |
| 0.0447 | 87.5 | 3500 | 0.4518 | 0.3461 |
| 0.0396 | 100.0 | 4000 | 0.4623 | 0.3420 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.4.dev0
- Tokenizers 0.11.0