metadata
language:
- ka
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Tiny Ka
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice
type: mozilla-foundation/common_voice_16_1
config: ka
split: test
args: ka
metrics:
- name: Wer
type: wer
value: 134.83959527973963
Whisper Tiny Ka
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice dataset. It achieves the following results on the evaluation set:
- Loss: 5.0988
- Wer: 134.8396
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: 0.003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 1000
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.0576 | 1.45 | 1000 | 5.1841 | 158.1475 |
| 4.6405 | 2.9 | 2000 | 4.8881 | 131.9237 |
| 4.0627 | 4.35 | 3000 | 4.9336 | 143.5772 |
| 3.781 | 5.8 | 4000 | 4.9113 | 129.0976 |
| 3.0831 | 7.25 | 5000 | 5.0988 | 134.8396 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.0.1+cu118
- Datasets 2.17.1
- Tokenizers 0.15.2