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asr-300m-turkish
This model is a fine-tuned version of wav2vec2 xls-r 300M on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.4060
- Wer: 0.3879
Model description
The following datasets were used for finetuning:
- Common Voice 7.0 TR All
validatedsplit excepttestsplit was used for training. - MediaSpeech
Intended uses & limitations
More information needed
Training and evaluation data
The following datasets were used for finetuning:
Common Voice 7.0 TR All validated split except test split was used for training. MediaSpeech
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.9649 | 4.26 | 400 | 0.7179 | 0.7544 |
| 0.3912 | 8.51 | 800 | 0.4798 | 0.5432 |
| 0.1848 | 12.77 | 1200 | 0.4588 | 0.4792 |
| 0.1277 | 17.02 | 1600 | 0.4676 | 0.4510 |
| 0.0923 | 21.28 | 2000 | 0.4251 | 0.4218 |
| 0.07 | 25.53 | 2400 | 0.4164 | 0.4006 |
| 0.0546 | 29.79 | 2800 | 0.4060 | 0.3879 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3
