metadata
language:
- ur
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Ur - TahaMan
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: ur
split: None
args: 'config: ur, split: test'
metrics:
- name: Wer
type: wer
value: 47.229551451187334
Whisper Small Ur - TahaMan
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9384
- Wer: 47.2296
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: 32
- eval_batch_size: 8
- 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: 50
- training_steps: 400
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7769 | 5.2632 | 50 | 0.7217 | 62.9288 |
| 0.1271 | 10.5263 | 100 | 0.7884 | 62.4011 |
| 0.0149 | 15.7895 | 150 | 0.8567 | 48.0211 |
| 0.0039 | 21.0526 | 200 | 0.8914 | 47.2296 |
| 0.0024 | 26.3158 | 250 | 0.9138 | 47.2296 |
| 0.0018 | 31.5789 | 300 | 0.9278 | 47.2296 |
| 0.0016 | 36.8421 | 350 | 0.9357 | 46.9657 |
| 0.0014 | 42.1053 | 400 | 0.9384 | 47.2296 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1