metadata
language:
- ml
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 Malayalam - Arjun Shaji
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: ml
split: None
args: 'config: ml, split: test'
metrics:
- name: Wer
type: wer
value: 83.9080459770115
Whisper Small Malayalam - Arjun Shaji
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: 0.5649
- Wer: 83.9080
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: 100
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8113 | 3.7037 | 100 | 0.5609 | 100.6897 |
| 0.1123 | 7.4074 | 200 | 0.4366 | 88.0460 |
| 0.0184 | 11.1111 | 300 | 0.4850 | 87.1264 |
| 0.0056 | 14.8148 | 400 | 0.5643 | 87.8161 |
| 0.001 | 18.5185 | 500 | 0.5649 | 83.9080 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1