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xlsr-syntesized-turkish-4-hour-llr
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.7455
- Wer: 1.0
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 9.2067 | 0.52 | 100 | 7.7166 | 1.0 |
| 4.7666 | 1.04 | 200 | 4.5059 | 1.0 |
| 3.6173 | 1.56 | 300 | 3.6445 | 1.0 |
| 3.3747 | 2.08 | 400 | 3.4531 | 1.0 |
| 3.2351 | 2.6 | 500 | 3.3077 | 1.0 |
| 3.16 | 3.12 | 600 | 3.1965 | 1.0 |
| 3.092 | 3.65 | 700 | 3.1473 | 1.0 |
| 3.0051 | 4.17 | 800 | 3.1395 | 1.0 |
| 2.785 | 4.69 | 900 | 3.2007 | 1.0 |
| 2.3783 | 5.21 | 1000 | 3.1456 | 1.0 |
| 2.0074 | 5.73 | 1100 | 3.0829 | 1.0 |
| 1.767 | 6.25 | 1200 | 3.0563 | 1.0 |
| 1.4704 | 6.77 | 1300 | 3.0522 | 1.0 |
| 1.2749 | 7.29 | 1400 | 3.1219 | 1.0 |
| 1.12 | 7.81 | 1500 | 3.1256 | 1.0 |
| 1.0151 | 8.33 | 1600 | 3.1973 | 1.0 |
| 0.9098 | 8.85 | 1700 | 3.2901 | 1.0 |
| 0.8451 | 9.38 | 1800 | 3.2970 | 1.0 |
| 0.793 | 9.9 | 1900 | 3.3592 | 1.0 |
| 0.7518 | 10.42 | 2000 | 3.4237 | 1.0 |
| 0.6994 | 10.94 | 2100 | 3.4695 | 1.0 |
| 0.6686 | 11.46 | 2200 | 3.5052 | 1.0 |
| 0.6558 | 11.98 | 2300 | 3.5431 | 1.0 |
| 0.6247 | 12.5 | 2400 | 3.6077 | 1.0 |
| 0.615 | 13.02 | 2500 | 3.6611 | 1.0 |
| 0.5889 | 13.54 | 2600 | 3.5684 | 1.0 |
| 0.5702 | 14.06 | 2700 | 3.5891 | 1.0 |
| 0.5552 | 14.58 | 2800 | 3.6027 | 1.0 |
| 0.5367 | 15.1 | 2900 | 3.6398 | 1.0 |
| 0.5322 | 15.62 | 3000 | 3.6480 | 1.0 |
| 0.5051 | 16.15 | 3100 | 3.6087 | 1.0 |
| 0.5063 | 16.67 | 3200 | 3.6777 | 1.0 |
| 0.4869 | 17.19 | 3300 | 3.6848 | 1.0 |
| 0.4945 | 17.71 | 3400 | 3.6886 | 1.0 |
| 0.4848 | 18.23 | 3500 | 3.7217 | 1.0 |
| 0.489 | 18.75 | 3600 | 3.7360 | 1.0 |
| 0.4811 | 19.27 | 3700 | 3.7442 | 1.0 |
| 0.4665 | 19.79 | 3800 | 3.7455 | 1.0 |
Framework versions
- Transformers 4.26.0
- Pytorch 2.0.1+cu118
- Datasets 2.9.0
- Tokenizers 0.13.3
