wav2vec2-large-xls-r-300m-turkish-colab_common_voice-8_6
This model is a fine-tuned version of husnu/wav2vec2-large-xls-r-300m-turkish-colab_common_voice-8_5 on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.3646
- Wer: 0.3478
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: 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: 6
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1024 | 0.51 | 400 | 0.4030 | 0.4171 |
0.1533 | 1.02 | 800 | 0.4733 | 0.4570 |
0.1584 | 1.53 | 1200 | 0.4150 | 0.4371 |
0.1538 | 2.04 | 1600 | 0.4104 | 0.4390 |
0.1395 | 2.55 | 2000 | 0.3891 | 0.4133 |
0.1415 | 3.07 | 2400 | 0.3877 | 0.4015 |
0.1261 | 3.58 | 2800 | 0.3685 | 0.3899 |
0.1149 | 4.09 | 3200 | 0.3791 | 0.3881 |
0.1003 | 4.6 | 3600 | 0.3642 | 0.3626 |
0.0934 | 5.11 | 4000 | 0.3755 | 0.3516 |
0.0805 | 5.62 | 4400 | 0.3646 | 0.3478 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 2.1.0
- Tokenizers 0.10.3
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