metadata
license: apache-2.0
base_model: smerchi/Arabic-Morocco-Speech_To_Text
tags:
- generated_from_trainer
datasets:
- eniafou/data_cleverlytics
metrics:
- wer
model-index:
- name: Arabic-Morocco-Speech_To_Text-2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: clevelytics-INWI
type: eniafou/data_cleverlytics
metrics:
- name: Wer
type: wer
value: 38.64455659697188
Arabic-Morocco-Speech_To_Text-2
This model is a fine-tuned version of smerchi/Arabic-Morocco-Speech_To_Text on the clevelytics-INWI dataset. It achieves the following results on the evaluation set:
- Loss: 0.5924
- Wer: 38.6446
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1426 | 1.0 | 30 | 0.5924 | 38.6446 |
| 0.044 | 2.0 | 60 | 0.6992 | 40.0865 |
| 0.0273 | 3.0 | 90 | 0.7299 | 41.5285 |
| 0.018 | 4.0 | 120 | 0.7187 | 39.9423 |
| 0.0072 | 5.0 | 150 | 0.7263 | 39.6539 |
| 0.0056 | 6.0 | 180 | 0.7556 | 40.1586 |
| 0.0037 | 7.0 | 210 | 0.7415 | 38.9329 |
| 0.0025 | 8.0 | 240 | 0.7665 | 38.9329 |
| 0.0011 | 9.0 | 270 | 0.7764 | 38.9329 |
| 0.0005 | 10.0 | 300 | 0.7848 | 39.9423 |
| 0.0004 | 11.0 | 330 | 0.7912 | 39.1492 |
| 0.0004 | 12.0 | 360 | 0.7953 | 39.3655 |
| 0.0004 | 13.0 | 390 | 0.7980 | 39.1492 |
| 0.0004 | 14.0 | 420 | 0.7998 | 39.2213 |
| 0.0003 | 15.0 | 450 | 0.8003 | 39.2213 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1