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 manju Mal
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: 99.08045977011494
Whisper Small manju Mal
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: 0.7138
- Wer: 99.0805
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: 6000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0069 | 37.0370 | 1000 | 0.6246 | 145.0575 |
| 0.0025 | 74.0741 | 2000 | 0.6177 | 99.3103 |
| 0.0 | 111.1111 | 3000 | 0.6737 | 101.3793 |
| 0.0 | 148.1481 | 4000 | 0.6957 | 99.0805 |
| 0.0 | 185.1852 | 5000 | 0.7087 | 99.3103 |
| 0.0 | 222.2222 | 6000 | 0.7138 | 99.0805 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1