|
--- |
|
tags: |
|
- generated_from_trainer |
|
base_model: batoula187/wav2vec2-large-xls-r-300m-arabic-colab |
|
datasets: |
|
- common_voice_12_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-large-xls-r-300m-arabic-colab |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: common_voice_12_0 |
|
type: common_voice_12_0 |
|
config: ar |
|
split: test[:10%] |
|
args: ar |
|
metrics: |
|
- type: wer |
|
value: 0.7661710754972002 |
|
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. --> |
|
|
|
# wav2vec2-large-xls-r-300m-arabic-colab |
|
|
|
This model is a fine-tuned version of [batoula187/wav2vec2-large-xls-r-300m-arabic-colab](https://huggingface.co/batoula187/wav2vec2-large-xls-r-300m-arabic-colab) on the common_voice_12_0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.0728 |
|
- Wer: 0.7662 |
|
|
|
## 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: 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 | |
|
|:-------------:|:-------:|:----:|:---------------:|:------:| |
|
| 0.1061 | 2.2599 | 200 | 1.8297 | 0.8034 | |
|
| 0.1496 | 4.5198 | 400 | 1.6173 | 0.7955 | |
|
| 0.2105 | 6.7797 | 600 | 1.6220 | 0.8040 | |
|
| 0.1798 | 9.0395 | 800 | 2.2087 | 0.8405 | |
|
| 0.1389 | 11.2994 | 1000 | 1.7900 | 0.7868 | |
|
| 0.1143 | 13.5593 | 1200 | 1.7566 | 0.7886 | |
|
| 0.103 | 15.8192 | 1400 | 1.8148 | 0.7689 | |
|
| 0.0904 | 18.0791 | 1600 | 1.8059 | 0.7627 | |
|
| 0.0766 | 20.3390 | 1800 | 2.1398 | 0.7907 | |
|
| 0.0682 | 22.5989 | 2000 | 2.0384 | 0.7779 | |
|
| 0.0583 | 24.8588 | 2200 | 2.0727 | 0.7658 | |
|
| 0.0575 | 27.1186 | 2400 | 2.1649 | 0.7758 | |
|
| 0.0582 | 29.3785 | 2600 | 2.0728 | 0.7662 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|