File size: 4,963 Bytes
e254d0e 824da00 e254d0e 824da00 e254d0e 824da00 e254d0e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 |
---
library_name: transformers
license: cc-by-nc-4.0
base_model: mms-meta/mms-zeroshot-300m
tags:
- automatic-speech-recognition
- BembaSpeech
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-zeroshot-300m-bem
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mms-zeroshot-300m-bem
This model is a fine-tuned version of [mms-meta/mms-zeroshot-300m](https://huggingface.co/mms-meta/mms-zeroshot-300m) on the BEMBASPEECH - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1787
- Wer: 0.3583
## 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: 4
- 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: 500
- num_epochs: 10.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 4.6629 | 0.1778 | 500 | 0.3540 | 0.5421 |
| 0.6579 | 0.3556 | 1000 | 0.2588 | 0.4883 |
| 0.591 | 0.5334 | 1500 | 0.2552 | 0.4720 |
| 0.5467 | 0.7112 | 2000 | 0.2370 | 0.4542 |
| 0.5405 | 0.8890 | 2500 | 0.2376 | 0.4556 |
| 0.5027 | 1.0669 | 3000 | 0.2234 | 0.4307 |
| 0.5001 | 1.2447 | 3500 | 0.2176 | 0.4213 |
| 0.4962 | 1.4225 | 4000 | 0.2199 | 0.4205 |
| 0.486 | 1.6003 | 4500 | 0.2145 | 0.4167 |
| 0.47 | 1.7781 | 5000 | 0.2159 | 0.4169 |
| 0.4557 | 1.9559 | 5500 | 0.2099 | 0.4135 |
| 0.4514 | 2.1337 | 6000 | 0.2091 | 0.4100 |
| 0.4539 | 2.3115 | 6500 | 0.2038 | 0.4016 |
| 0.439 | 2.4893 | 7000 | 0.2041 | 0.4025 |
| 0.4378 | 2.6671 | 7500 | 0.2002 | 0.3916 |
| 0.4347 | 2.8450 | 8000 | 0.1961 | 0.3911 |
| 0.4278 | 3.0228 | 8500 | 0.1995 | 0.3923 |
| 0.4117 | 3.2006 | 9000 | 0.1959 | 0.3892 |
| 0.4149 | 3.3784 | 9500 | 0.1926 | 0.3859 |
| 0.4148 | 3.5562 | 10000 | 0.1958 | 0.3804 |
| 0.4009 | 3.7340 | 10500 | 0.1930 | 0.3790 |
| 0.4174 | 3.9118 | 11000 | 0.1955 | 0.3823 |
| 0.4012 | 4.0896 | 11500 | 0.1950 | 0.3812 |
| 0.3974 | 4.2674 | 12000 | 0.1934 | 0.3773 |
| 0.3943 | 4.4452 | 12500 | 0.1845 | 0.3720 |
| 0.4071 | 4.6230 | 13000 | 0.1920 | 0.3839 |
| 0.3968 | 4.8009 | 13500 | 0.1867 | 0.3743 |
| 0.3795 | 4.9787 | 14000 | 0.1872 | 0.3713 |
| 0.3856 | 5.1565 | 14500 | 0.1869 | 0.3737 |
| 0.3706 | 5.3343 | 15000 | 0.1903 | 0.3766 |
| 0.3784 | 5.5121 | 15500 | 0.1861 | 0.3683 |
| 0.3777 | 5.6899 | 16000 | 0.1866 | 0.3713 |
| 0.3861 | 5.8677 | 16500 | 0.1812 | 0.3637 |
| 0.3711 | 6.0455 | 17000 | 0.1842 | 0.3667 |
| 0.374 | 6.2233 | 17500 | 0.1815 | 0.3618 |
| 0.3539 | 6.4011 | 18000 | 0.1815 | 0.3647 |
| 0.3625 | 6.5789 | 18500 | 0.1785 | 0.3589 |
| 0.3599 | 6.7568 | 19000 | 0.1795 | 0.3621 |
| 0.3654 | 6.9346 | 19500 | 0.1822 | 0.3624 |
| 0.3693 | 7.1124 | 20000 | 0.1792 | 0.3612 |
| 0.3519 | 7.2902 | 20500 | 0.1800 | 0.3675 |
| 0.3553 | 7.4680 | 21000 | 0.1808 | 0.3640 |
| 0.3451 | 7.6458 | 21500 | 0.1808 | 0.3620 |
| 0.3558 | 7.8236 | 22000 | 0.1794 | 0.3610 |
| 0.3595 | 8.0014 | 22500 | 0.1772 | 0.3576 |
| 0.3404 | 8.1792 | 23000 | 0.1788 | 0.3581 |
| 0.3593 | 8.3570 | 23500 | 0.1782 | 0.3580 |
| 0.3471 | 8.5349 | 24000 | 0.1797 | 0.3606 |
| 0.3497 | 8.7127 | 24500 | 0.1778 | 0.3588 |
| 0.3398 | 8.8905 | 25000 | 0.1775 | 0.3583 |
| 0.3444 | 9.0683 | 25500 | 0.1796 | 0.3586 |
| 0.3366 | 9.2461 | 26000 | 0.1785 | 0.3574 |
| 0.3434 | 9.4239 | 26500 | 0.1781 | 0.3592 |
| 0.3426 | 9.6017 | 27000 | 0.1786 | 0.3593 |
| 0.3496 | 9.7795 | 27500 | 0.1787 | 0.3590 |
| 0.334 | 9.9573 | 28000 | 0.1788 | 0.3588 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
|