|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice_16_0 |
|
metrics: |
|
- wer |
|
base_model: facebook/w2v-bert-2.0 |
|
model-index: |
|
- name: w2v-bert-2.0-swahili-colab-CV16.0_5epochs |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: common_voice_16_0 |
|
type: common_voice_16_0 |
|
config: sw |
|
split: test |
|
args: sw |
|
metrics: |
|
- type: wer |
|
value: 0.8218669188312941 |
|
name: Wer |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# w2v-bert-2.0-swahili-colab-CV16.0_5epochs |
|
|
|
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_16_0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: inf |
|
- Wer: 0.8219 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 5 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 2.015 | 0.16 | 300 | inf | 0.2387 | |
|
| 0.2497 | 0.33 | 600 | inf | 0.2413 | |
|
| 0.2246 | 0.49 | 900 | inf | 0.2121 | |
|
| 0.2032 | 0.66 | 1200 | inf | 0.2097 | |
|
| 0.1895 | 0.82 | 1500 | inf | 0.1969 | |
|
| 0.1897 | 0.99 | 1800 | inf | 0.2092 | |
|
| 0.1718 | 1.15 | 2100 | inf | 0.1895 | |
|
| 0.1872 | 1.31 | 2400 | inf | 0.1949 | |
|
| 0.2056 | 1.48 | 2700 | inf | 0.1975 | |
|
| 0.3533 | 1.64 | 3000 | inf | 0.4304 | |
|
| 0.5492 | 1.81 | 3300 | inf | 0.2979 | |
|
| 1.0312 | 1.97 | 3600 | inf | 0.5560 | |
|
| 0.8936 | 2.14 | 3900 | inf | 0.8217 | |
|
| 1.0655 | 2.3 | 4200 | inf | 0.8219 | |
|
| 1.0856 | 2.46 | 4500 | inf | 0.8219 | |
|
| 1.0855 | 2.63 | 4800 | inf | 0.8219 | |
|
| 1.0823 | 2.79 | 5100 | inf | 0.8219 | |
|
| 1.0847 | 2.96 | 5400 | inf | 0.8219 | |
|
| 1.0835 | 3.12 | 5700 | inf | 0.8219 | |
|
| 1.0886 | 3.28 | 6000 | inf | 0.8219 | |
|
| 1.0801 | 3.45 | 6300 | inf | 0.8219 | |
|
| 1.0765 | 3.61 | 6600 | inf | 0.8219 | |
|
| 1.0878 | 3.78 | 6900 | inf | 0.8219 | |
|
| 1.0884 | 3.94 | 7200 | inf | 0.8219 | |
|
| 1.0824 | 4.11 | 7500 | inf | 0.8219 | |
|
| 1.0881 | 4.27 | 7800 | inf | 0.8219 | |
|
| 1.0884 | 4.43 | 8100 | inf | 0.8219 | |
|
| 1.0786 | 4.6 | 8400 | inf | 0.8219 | |
|
| 1.0846 | 4.76 | 8700 | inf | 0.8219 | |
|
| 1.0861 | 4.93 | 9000 | inf | 0.8219 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.1 |
|
- Pytorch 2.1.1+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.0 |
|
|
