|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice |
|
model-index: |
|
- name: wav2vec2_Indonesia_4 |
|
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. --> |
|
|
|
# wav2vec2_Indonesia_4 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.3147 |
|
- Wer: 0.5914 |
|
|
|
## Model description |
|
|
|
Model yang dilatih dengan data train common voice dan data test data perkuliahan |
|
|
|
## 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: 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: 30 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 3.9949 | 3.23 | 400 | 1.3340 | 0.8916 | |
|
| 0.4469 | 6.45 | 800 | 1.0507 | 0.6859 | |
|
| 0.2003 | 9.68 | 1200 | 1.1115 | 0.6369 | |
|
| 0.1432 | 12.9 | 1600 | 1.1307 | 0.6297 | |
|
| 0.1138 | 16.13 | 2000 | 1.2157 | 0.6369 | |
|
| 0.089 | 19.35 | 2400 | 1.2834 | 0.6058 | |
|
| 0.0712 | 22.58 | 2800 | 1.3283 | 0.5947 | |
|
| 0.057 | 25.81 | 3200 | 1.3345 | 0.5827 | |
|
| 0.0467 | 29.03 | 3600 | 1.3147 | 0.5914 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.11.3 |
|
- Pytorch 1.10.0+cu113 |
|
- Datasets 1.18.3 |
|
- Tokenizers 0.10.3 |
|
|
