File size: 3,283 Bytes
165c4a4 cb4766d 165c4a4 cb4766d |
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 |
---
library_name: transformers
language:
- lg
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
datasets:
- yogera
metrics:
- wer
model-index:
- name: wav2vec2-bert
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Yogera
type: yogera
metrics:
- name: Wer
type: wer
value: 0.1597164303586322
---
<!-- 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. -->
# wav2vec2-bert
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the Yogera dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2858
- Wer: 0.1597
- Cer: 0.0355
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.8824 | 1.0 | 198 | 0.2803 | 0.2968 | 0.0591 |
| 0.2156 | 2.0 | 396 | 0.2128 | 0.2389 | 0.0493 |
| 0.1589 | 3.0 | 594 | 0.2110 | 0.2207 | 0.0458 |
| 0.1277 | 4.0 | 792 | 0.1942 | 0.1964 | 0.0422 |
| 0.1055 | 5.0 | 990 | 0.1698 | 0.1873 | 0.0390 |
| 0.087 | 6.0 | 1188 | 0.1771 | 0.1879 | 0.0428 |
| 0.0738 | 7.0 | 1386 | 0.1850 | 0.1856 | 0.0406 |
| 0.0589 | 8.0 | 1584 | 0.1799 | 0.1681 | 0.0381 |
| 0.0573 | 9.0 | 1782 | 0.1882 | 0.1863 | 0.0400 |
| 0.0481 | 10.0 | 1980 | 0.2275 | 0.1664 | 0.0359 |
| 0.0425 | 11.0 | 2178 | 0.2135 | 0.1696 | 0.0379 |
| 0.039 | 12.0 | 2376 | 0.2035 | 0.1600 | 0.0354 |
| 0.0351 | 13.0 | 2574 | 0.2095 | 0.1683 | 0.0366 |
| 0.0326 | 14.0 | 2772 | 0.2070 | 0.1589 | 0.0353 |
| 0.0302 | 15.0 | 2970 | 0.2526 | 0.1708 | 0.0367 |
| 0.0308 | 16.0 | 3168 | 0.2441 | 0.1642 | 0.0367 |
| 0.0255 | 17.0 | 3366 | 0.2504 | 0.1678 | 0.0365 |
| 0.0213 | 18.0 | 3564 | 0.2844 | 0.1721 | 0.0377 |
| 0.0225 | 19.0 | 3762 | 0.2602 | 0.1721 | 0.0383 |
| 0.02 | 20.0 | 3960 | 0.2746 | 0.1610 | 0.0351 |
| 0.0181 | 21.0 | 4158 | 0.2767 | 0.1668 | 0.0364 |
| 0.0149 | 22.0 | 4356 | 0.2442 | 0.1633 | 0.0355 |
| 0.0136 | 23.0 | 4554 | 0.2765 | 0.1677 | 0.0362 |
| 0.0156 | 24.0 | 4752 | 0.2858 | 0.1597 | 0.0355 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.1.0+cu118
- Datasets 3.0.1
- Tokenizers 0.20.1
|