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wav2vec2-finetune-XLSR_maroc
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2804
- Wer: 0.3265
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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.9859 | 0.83 | 400 | 2.0919 | 0.9982 |
| 0.8639 | 1.66 | 800 | 0.4365 | 0.5925 |
| 0.4879 | 2.49 | 1200 | 0.3467 | 0.5079 |
| 0.3732 | 3.32 | 1600 | 0.3267 | 0.4756 |
| 0.314 | 4.15 | 2000 | 0.2835 | 0.4314 |
| 0.274 | 4.97 | 2400 | 0.2915 | 0.4364 |
| 0.2463 | 5.8 | 2800 | 0.3050 | 0.4277 |
| 0.2354 | 6.63 | 3200 | 0.2766 | 0.4179 |
| 0.2101 | 7.46 | 3600 | 0.2896 | 0.4071 |
| 0.1976 | 8.29 | 4000 | 0.2856 | 0.4099 |
| 0.186 | 9.12 | 4400 | 0.2849 | 0.3987 |
| 0.1758 | 9.95 | 4800 | 0.2819 | 0.4026 |
| 0.1667 | 10.78 | 5200 | 0.2869 | 0.3934 |
| 0.1508 | 11.61 | 5600 | 0.2793 | 0.3851 |
| 0.1468 | 12.44 | 6000 | 0.2777 | 0.3836 |
| 0.1322 | 13.26 | 6400 | 0.2731 | 0.3767 |
| 0.1295 | 14.09 | 6800 | 0.2833 | 0.3741 |
| 0.1157 | 14.92 | 7200 | 0.2815 | 0.3786 |
| 0.1147 | 15.75 | 7600 | 0.2684 | 0.3741 |
| 0.1099 | 16.58 | 8000 | 0.2704 | 0.3677 |
| 0.1056 | 17.41 | 8400 | 0.2744 | 0.3668 |
| 0.0983 | 18.24 | 8800 | 0.2675 | 0.3676 |
| 0.0975 | 19.07 | 9200 | 0.2787 | 0.3588 |
| 0.0906 | 19.9 | 9600 | 0.2749 | 0.3537 |
| 0.0862 | 20.73 | 10000 | 0.2875 | 0.3557 |
| 0.0812 | 21.55 | 10400 | 0.2863 | 0.3482 |
| 0.0761 | 22.38 | 10800 | 0.2739 | 0.3513 |
| 0.0738 | 23.21 | 11200 | 0.2878 | 0.3467 |
| 0.0678 | 24.04 | 11600 | 0.2886 | 0.3399 |
| 0.0661 | 24.87 | 12000 | 0.2958 | 0.3380 |
| 0.0623 | 25.7 | 12400 | 0.2779 | 0.3354 |
| 0.0586 | 26.53 | 12800 | 0.2871 | 0.3333 |
| 0.0563 | 27.36 | 13200 | 0.2895 | 0.3316 |
| 0.0554 | 28.19 | 13600 | 0.2846 | 0.3277 |
| 0.0522 | 29.02 | 14000 | 0.2752 | 0.3276 |
| 0.0498 | 29.84 | 14400 | 0.2804 | 0.3265 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
