|
|
--- |
|
|
license: cc-by-nc-4.0 |
|
|
base_model: facebook/mms-1b-all |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- common_voice_11_0 |
|
|
metrics: |
|
|
- wer |
|
|
model-index: |
|
|
- name: wav2vec2-kyrgyz-colab |
|
|
results: |
|
|
- task: |
|
|
name: Automatic Speech Recognition |
|
|
type: automatic-speech-recognition |
|
|
dataset: |
|
|
name: common_voice_11_0 |
|
|
type: common_voice_11_0 |
|
|
config: ky |
|
|
split: test |
|
|
args: ky |
|
|
metrics: |
|
|
- name: Wer |
|
|
type: wer |
|
|
value: 0.26476260446321975 |
|
|
--- |
|
|
|
|
|
<!-- 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-kyrgyz-colab |
|
|
|
|
|
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_11_0 dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.2952 |
|
|
- Wer: 0.2648 |
|
|
|
|
|
## 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: 1e-05 |
|
|
- train_batch_size: 2 |
|
|
- 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: 200 |
|
|
- num_epochs: 5 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
|
| 9.9224 | 0.29 | 500 | 3.9047 | 1.0023 | |
|
|
| 3.3028 | 0.59 | 1000 | 2.7653 | 0.9997 | |
|
|
| 2.4414 | 0.88 | 1500 | 1.1551 | 0.6330 | |
|
|
| 1.5571 | 1.18 | 2000 | 0.5679 | 0.3712 | |
|
|
| 1.2479 | 1.47 | 2500 | 0.4202 | 0.3291 | |
|
|
| 1.0857 | 1.76 | 3000 | 0.3655 | 0.3105 | |
|
|
| 1.0304 | 2.06 | 3500 | 0.3392 | 0.3007 | |
|
|
| 0.9989 | 2.35 | 4000 | 0.3245 | 0.2909 | |
|
|
| 0.9711 | 2.65 | 4500 | 0.3157 | 0.2825 | |
|
|
| 0.9371 | 2.94 | 5000 | 0.3093 | 0.2764 | |
|
|
| 0.9423 | 3.24 | 5500 | 0.3047 | 0.2732 | |
|
|
| 0.9226 | 3.53 | 6000 | 0.3017 | 0.2715 | |
|
|
| 0.9365 | 3.82 | 6500 | 0.2990 | 0.2689 | |
|
|
| 0.8969 | 4.12 | 7000 | 0.2971 | 0.2668 | |
|
|
| 0.9101 | 4.41 | 7500 | 0.2961 | 0.2644 | |
|
|
| 0.9044 | 4.71 | 8000 | 0.2954 | 0.2642 | |
|
|
| 0.902 | 5.0 | 8500 | 0.2952 | 0.2648 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.37.0.dev0 |
|
|
- Pytorch 2.1.2+cu121 |
|
|
- Datasets 2.16.1 |
|
|
- Tokenizers 0.15.0 |
|
|
|
