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wav2vec2-large-xls-r-300m-Arabic-phoneme-based
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: 0.7493
- Per: 0.1979
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: 0.0005
- train_batch_size: 2
- eval_batch_size: 6
- 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: 250
- num_epochs: 30.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Per |
|---|---|---|---|---|
| 1.9601 | 1.0 | 2187 | 1.7221 | 0.9190 |
| 1.307 | 2.0 | 4374 | 1.0964 | 0.4532 |
| 0.9363 | 3.0 | 6561 | 0.9163 | 0.3469 |
| 0.7942 | 4.0 | 8748 | 0.8432 | 0.3037 |
| 0.7 | 5.0 | 10935 | 0.7827 | 0.2881 |
| 0.6274 | 6.0 | 13122 | 0.7456 | 0.2713 |
| 0.5692 | 7.0 | 15309 | 0.6924 | 0.2572 |
| 0.5203 | 8.0 | 17496 | 0.6521 | 0.2491 |
| 0.4853 | 9.0 | 19683 | 0.6583 | 0.2420 |
| 0.4448 | 10.0 | 21870 | 0.6580 | 0.2312 |
| 0.4134 | 11.0 | 24057 | 0.6313 | 0.2380 |
| 0.389 | 12.0 | 26244 | 0.6099 | 0.2225 |
| 0.3644 | 13.0 | 28431 | 0.6238 | 0.2239 |
| 0.3432 | 14.0 | 30618 | 0.6369 | 0.2195 |
| 0.3191 | 15.0 | 32805 | 0.6391 | 0.2164 |
| 0.2992 | 16.0 | 34992 | 0.6314 | 0.2164 |
| 0.2827 | 17.0 | 37179 | 0.6385 | 0.2143 |
| 0.2666 | 18.0 | 39366 | 0.6330 | 0.2159 |
| 0.2479 | 19.0 | 41553 | 0.6653 | 0.2125 |
| 0.2341 | 20.0 | 43740 | 0.6692 | 0.2165 |
| 0.2209 | 21.0 | 45927 | 0.6656 | 0.2199 |
| 0.2075 | 22.0 | 48114 | 0.6669 | 0.2104 |
| 0.1955 | 23.0 | 50301 | 0.6830 | 0.2044 |
| 0.1825 | 24.0 | 52488 | 0.6973 | 0.2065 |
| 0.1758 | 25.0 | 54675 | 0.7265 | 0.2013 |
| 0.1644 | 26.0 | 56862 | 0.7416 | 0.2040 |
| 0.1571 | 27.0 | 59049 | 0.7202 | 0.2007 |
| 0.1489 | 28.0 | 61236 | 0.7224 | 0.2019 |
| 0.1432 | 29.0 | 63423 | 0.7357 | 0.1988 |
| 0.1373 | 30.0 | 65610 | 0.7493 | 0.1979 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3
