metadata
license: apache-2.0
base_model: arun100/whisper-small-fa-2
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small Persian Iranian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs fa_ir
type: google/fleurs
config: fa_ir
split: test
args: fa_ir
metrics:
- name: Wer
type: wer
value: 26.412935323383085
Whisper Small Persian Iranian
This model is a fine-tuned version of arun100/whisper-small-fa-2 on the google/fleurs fa_ir dataset. It achieves the following results on the evaluation set:
- Loss: 0.3192
- Wer: 26.4129
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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0865 | 43.0 | 500 | 0.3192 | 26.4129 |
| 0.008 | 86.0 | 1000 | 0.3816 | 27.0149 |
| 0.0033 | 130.0 | 1500 | 0.4108 | 27.2289 |
| 0.0019 | 173.0 | 2000 | 0.4313 | 27.4030 |
| 0.0013 | 217.0 | 2500 | 0.4479 | 27.5323 |
| 0.001 | 260.0 | 3000 | 0.4612 | 27.5423 |
| 0.0008 | 304.0 | 3500 | 0.4719 | 27.7861 |
| 0.0006 | 347.0 | 4000 | 0.4802 | 27.9900 |
| 0.0006 | 391.0 | 4500 | 0.4859 | 27.9502 |
| 0.0005 | 434.0 | 5000 | 0.4882 | 27.9154 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0