metadata
language:
- id
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Id - Fine Tuned - Revised
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 13
type: mozilla-foundation/common_voice_13_0
config: id
split: validation
args: id
metrics:
- name: Wer
type: wer
value: 18.470763265858167
Whisper Small Id - Fine Tuned - Revised
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3528
- Wer Ortho: 22.8496
- Wer: 18.4708
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.3546 | 0.7911 | 250 | 0.3433 | 23.8195 | 18.6421 |
| 0.1621 | 1.5823 | 500 | 0.3325 | 23.2594 | 18.9171 |
| 0.058 | 2.3734 | 750 | 0.3483 | 23.1274 | 18.0966 |
| 0.0265 | 3.1646 | 1000 | 0.3528 | 22.8496 | 18.4708 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1