metadata
language:
- tr
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
- tr
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-base-turkish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice tr
type: common_voice
args: tr
metrics:
- name: Test WER
type: wer
value: 11.18
- name: Test CER
type: cer
value: 3.31
This model is a fine-tuned version of cahya/wav2vec2-base-turkish-artificial-cv on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:
- Loss: 0.1608
- Wer: 0.1395
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: 7.5e-06
- train_batch_size: 6
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.1224 | 3.45 | 500 | 0.1641 | 0.1396 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3