metadata
language:
- ml
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- CXDuncan/Malayalam-IndicVoices
metrics:
- wer
model-index:
- name: Whisper Small Malayalam
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Malayalam-IndicVoices
type: CXDuncan/Malayalam-IndicVoices
config: default
split: None
args: 'config: ml, split: test'
metrics:
- name: Wer
type: wer
value: 51.52998332245667
Whisper Small Malayalam
This model is a fine-tuned version of openai/whisper-small on the Malayalam-IndicVoices dataset. It achieves the following results on the evaluation set:
- Loss: 0.0003
- Wer: 51.5300
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0665 | 5.0 | 1000 | 0.0446 | 67.4679 |
| 0.0099 | 10.0 | 2000 | 0.0064 | 57.3925 |
| 0.0007 | 15.0 | 3000 | 0.0007 | 51.2762 |
| 0.0003 | 20.0 | 4000 | 0.0003 | 51.5300 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1