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xlsr-syntesized-turkish-4-hour-llr-2
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: 0.3600
- Wer: 0.3908
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: 0.0025
- 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 |
|---|---|---|---|---|
| 3.8281 | 0.52 | 100 | 3.0184 | 1.0 |
| 2.9829 | 1.04 | 200 | 2.7322 | 1.0 |
| 1.9671 | 1.56 | 300 | 0.9112 | 0.9752 |
| 0.846 | 2.08 | 400 | 0.5559 | 0.7995 |
| 0.6572 | 2.6 | 500 | 0.4549 | 0.7173 |
| 0.6061 | 3.12 | 600 | 0.4026 | 0.6306 |
| 0.5277 | 3.65 | 700 | 0.3818 | 0.5686 |
| 0.482 | 4.17 | 800 | 0.3699 | 0.5591 |
| 0.423 | 4.69 | 900 | 0.3543 | 0.5409 |
| 0.4262 | 5.21 | 1000 | 0.3444 | 0.5281 |
| 0.3991 | 5.73 | 1100 | 0.3637 | 0.5318 |
| 0.3954 | 6.25 | 1200 | 0.3564 | 0.5162 |
| 0.3503 | 6.77 | 1300 | 0.3861 | 0.6283 |
| 0.341 | 7.29 | 1400 | 0.3381 | 0.4984 |
| 0.3199 | 7.81 | 1500 | 0.3075 | 0.4844 |
| 0.3068 | 8.33 | 1600 | 0.2926 | 0.4610 |
| 0.3069 | 8.85 | 1700 | 0.3056 | 0.4693 |
| 0.2738 | 9.38 | 1800 | 0.3055 | 0.4649 |
| 0.2783 | 9.9 | 1900 | 0.2932 | 0.4420 |
| 0.2467 | 10.42 | 2000 | 0.2955 | 0.4283 |
| 0.237 | 10.94 | 2100 | 0.3103 | 0.4512 |
| 0.2284 | 11.46 | 2200 | 0.3228 | 0.4406 |
| 0.2296 | 11.98 | 2300 | 0.3204 | 0.4180 |
| 0.2078 | 12.5 | 2400 | 0.3491 | 0.4189 |
| 0.2142 | 13.02 | 2500 | 0.3304 | 0.4480 |
| 0.1983 | 13.54 | 2600 | 0.3364 | 0.4770 |
| 0.1913 | 14.06 | 2700 | 0.3099 | 0.4328 |
| 0.1763 | 14.58 | 2800 | 0.3127 | 0.3946 |
| 0.1749 | 15.1 | 2900 | 0.3274 | 0.4017 |
| 0.1616 | 15.62 | 3000 | 0.3419 | 0.3930 |
| 0.16 | 16.15 | 3100 | 0.3543 | 0.3904 |
| 0.1509 | 16.67 | 3200 | 0.3532 | 0.3951 |
| 0.1459 | 17.19 | 3300 | 0.3593 | 0.3959 |
| 0.1402 | 17.71 | 3400 | 0.3685 | 0.3964 |
| 0.1364 | 18.23 | 3500 | 0.3679 | 0.3942 |
| 0.141 | 18.75 | 3600 | 0.3662 | 0.3890 |
| 0.1348 | 19.27 | 3700 | 0.3656 | 0.3916 |
| 0.1331 | 19.79 | 3800 | 0.3600 | 0.3908 |
Framework versions
- Transformers 4.26.0
- Pytorch 2.1.0+cu118
- Datasets 2.9.0
- Tokenizers 0.13.3
