metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: nyankole_wav2vec2
results: []
nyankole_wav2vec2
This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.8606
- 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 55
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 7.4272 | 0.4739 | 50 | 2.9131 | 1.0 |
| 2.8729 | 0.9479 | 100 | 2.8567 | 1.0 |
| 2.9027 | 1.4218 | 150 | 2.9014 | 1.0 |
| 2.8676 | 1.8957 | 200 | 2.8607 | 1.0 |
| 2.8484 | 2.3697 | 250 | 2.8482 | 1.0 |
| 2.8807 | 2.8436 | 300 | 2.8553 | 1.0 |
| 2.8513 | 3.3175 | 350 | 2.8731 | 1.0 |
| 2.8489 | 3.7915 | 400 | 2.8524 | 1.0 |
| 2.841 | 4.2654 | 450 | 2.8468 | 1.0 |
| 2.9182 | 4.7393 | 500 | 2.8572 | 1.0 |
| 2.8441 | 5.2133 | 550 | 2.8642 | 1.0 |
| 2.8486 | 5.6872 | 600 | 2.8690 | 1.0 |
| 2.8455 | 6.1611 | 650 | 2.8663 | 1.0 |
| 2.845 | 6.6351 | 700 | 2.8611 | 1.0 |
| 2.856 | 7.1090 | 750 | 2.8781 | 1.0 |
| 2.8429 | 7.5829 | 800 | 2.8612 | 1.0 |
| 2.8456 | 8.0569 | 850 | 2.8555 | 1.0 |
| 2.8465 | 8.5308 | 900 | 2.8596 | 1.0 |
| 2.8465 | 9.0047 | 950 | 2.8507 | 1.0 |
| 2.848 | 9.4787 | 1000 | 2.8527 | 1.0 |
| 2.8441 | 9.9526 | 1050 | 2.8702 | 1.0 |
| 2.8452 | 10.4265 | 1100 | 2.8782 | 1.0 |
| 2.8446 | 10.9005 | 1150 | 2.8736 | 1.0 |
| 2.8433 | 11.3744 | 1200 | 2.8541 | 1.0 |
| 2.842 | 11.8483 | 1250 | 2.8678 | 1.0 |
| 2.8442 | 12.3223 | 1300 | 2.8559 | 1.0 |
| 2.8473 | 12.7962 | 1350 | 2.8538 | 1.0 |
| 2.843 | 13.2701 | 1400 | 2.8592 | 1.0 |
| 2.8429 | 13.7441 | 1450 | 2.8571 | 1.0 |
| 2.8431 | 14.2180 | 1500 | 2.8860 | 1.0 |
| 2.8428 | 14.6919 | 1550 | 2.8611 | 1.0 |
| 2.8429 | 15.1659 | 1600 | 2.8763 | 1.0 |
| 2.8387 | 15.6398 | 1650 | 2.8637 | 1.0 |
| 2.8503 | 16.1137 | 1700 | 2.8588 | 1.0 |
| 2.8463 | 16.5877 | 1750 | 2.8560 | 1.0 |
| 2.8414 | 17.0616 | 1800 | 2.8550 | 1.0 |
| 2.8417 | 17.5355 | 1850 | 2.8582 | 1.0 |
| 2.8438 | 18.0095 | 1900 | 2.8502 | 1.0 |
| 2.8497 | 18.4834 | 1950 | 2.8825 | 1.0 |
| 2.8377 | 18.9573 | 2000 | 2.8622 | 1.0 |
| 2.8412 | 19.4313 | 2050 | 2.8711 | 1.0 |
| 2.8405 | 19.9052 | 2100 | 2.8786 | 1.0 |
| 2.8419 | 20.3791 | 2150 | 2.8467 | 1.0 |
| 2.8426 | 20.8531 | 2200 | 2.8627 | 1.0 |
| 2.8454 | 21.3270 | 2250 | 2.8640 | 1.0 |
| 2.8397 | 21.8009 | 2300 | 2.8600 | 1.0 |
| 2.8405 | 22.2749 | 2350 | 2.8716 | 1.0 |
| 2.8413 | 22.7488 | 2400 | 2.8498 | 1.0 |
| 2.8454 | 23.2227 | 2450 | 2.8647 | 1.0 |
| 2.8415 | 23.6967 | 2500 | 2.8727 | 1.0 |
| 2.8381 | 24.1706 | 2550 | 2.8600 | 1.0 |
| 2.8405 | 24.6445 | 2600 | 2.8604 | 1.0 |
| 2.8442 | 25.1185 | 2650 | 2.8543 | 1.0 |
| 2.836 | 25.5924 | 2700 | 2.8613 | 1.0 |
| 2.8479 | 26.0664 | 2750 | 2.8664 | 1.0 |
| 2.842 | 26.5403 | 2800 | 2.8574 | 1.0 |
| 2.8406 | 27.0142 | 2850 | 2.8558 | 1.0 |
| 2.8435 | 27.4882 | 2900 | 2.8587 | 1.0 |
| 2.8387 | 27.9621 | 2950 | 2.8568 | 1.0 |
| 2.8442 | 28.4360 | 3000 | 2.8573 | 1.0 |
| 2.8365 | 28.9100 | 3050 | 2.8591 | 1.0 |
| 2.8428 | 29.3839 | 3100 | 2.8621 | 1.0 |
| 2.8386 | 29.8578 | 3150 | 2.8606 | 1.0 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1