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wav2vec2-large-mms-1b-barwar
This model is a fine-tuned version of facebook/mms-1b-all on the nena_speech_1_0_test dataset. It achieves the following results on the evaluation set:
- Loss: 3.4355
- Wer: 1.0
- Cer: 0.3295
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: 0.001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 16.2134 | 0.15 | 25 | 17.6705 | 1.0 | 1.1562 |
| 6.1907 | 0.3 | 50 | 4.2262 | 0.9815 | 0.9986 |
| 3.6438 | 0.45 | 75 | 4.1625 | 1.0 | 0.7804 |
| 3.1627 | 0.6 | 100 | 4.1537 | 1.0 | 0.4727 |
| 2.2322 | 0.75 | 125 | 3.8028 | 1.0 | 0.4554 |
| 3.0705 | 0.9 | 150 | 3.3680 | 1.0 | 0.4352 |
| 2.9176 | 1.05 | 175 | 3.2934 | 1.0 | 0.4279 |
| 2.2255 | 1.2 | 200 | 3.6359 | 1.0 | 0.3926 |
| 2.4518 | 1.35 | 225 | 3.2249 | 1.0 | 0.3863 |
| 1.9254 | 1.5 | 250 | 3.7029 | 1.0 | 0.3875 |
| 2.7212 | 1.65 | 275 | 3.5201 | 1.0 | 0.3673 |
| 2.7976 | 1.8 | 300 | 3.3253 | 1.0 | 0.3986 |
| 2.0545 | 1.95 | 325 | 3.6138 | 1.0 | 0.3554 |
| 2.3335 | 2.1 | 350 | 3.5161 | 1.0 | 0.3554 |
| 2.0049 | 2.25 | 375 | 3.4727 | 1.0 | 0.3543 |
| 2.8896 | 2.4 | 400 | 3.2484 | 1.0 | 0.3535 |
| 1.9641 | 2.54 | 425 | 3.4330 | 1.0 | 0.3485 |
| 1.9649 | 2.69 | 450 | 3.8596 | 1.0 | 0.3444 |
| 2.0422 | 2.84 | 475 | 3.4291 | 1.0 | 0.3506 |
| 2.4093 | 2.99 | 500 | 3.3137 | 1.0 | 0.3434 |
| 1.8187 | 3.14 | 525 | 3.4423 | 1.0 | 0.3415 |
| 1.7495 | 3.29 | 550 | 3.5614 | 1.0 | 0.3431 |
| 2.0658 | 3.44 | 575 | 3.0324 | 1.0 | 0.3543 |
| 1.5128 | 3.59 | 600 | 3.6654 | 1.0 | 0.3452 |
| 1.7876 | 3.74 | 625 | 3.8747 | 1.0 | 0.3388 |
| 3.8652 | 3.89 | 650 | 2.9874 | 1.0 | 0.3387 |
| 2.8945 | 4.04 | 675 | 3.3015 | 1.0 | 0.3344 |
| 1.9763 | 4.19 | 700 | 3.1970 | 1.0 | 0.3389 |
| 2.0538 | 4.34 | 725 | 3.4811 | 1.0 | 0.3316 |
| 1.7723 | 4.49 | 750 | 3.6706 | 1.0 | 0.3305 |
| 2.0489 | 4.64 | 775 | 3.4281 | 1.0 | 0.3312 |
| 2.555 | 4.79 | 800 | 3.2610 | 1.0 | 0.3341 |
| 1.6591 | 4.94 | 825 | 3.4355 | 1.0 | 0.3295 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
