metadata
library_name: transformers
language:
- id
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Tiny - FineTuned - Id -
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
args: 'config: id, split: test'
metrics:
- name: Wer
type: wer
value: 65.57659208261619
Whisper Tiny - FineTuned - Id -
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0871
- Wer: 65.5766
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.1857 | 1.5873 | 100 | 0.9525 | 64.8881 |
| 0.5773 | 3.1746 | 200 | 0.9205 | 59.1222 |
| 0.2841 | 4.7619 | 300 | 0.9536 | 59.2943 |
| 0.138 | 6.3492 | 400 | 0.9851 | 54.3890 |
| 0.0694 | 7.9365 | 500 | 1.0057 | 59.6386 |
| 0.0339 | 9.5238 | 600 | 1.0530 | 64.8021 |
| 0.0195 | 11.1111 | 700 | 1.0620 | 61.1876 |
| 0.013 | 12.6984 | 800 | 1.0752 | 57.1429 |
| 0.0106 | 14.2857 | 900 | 1.0827 | 65.4045 |
| 0.0097 | 15.8730 | 1000 | 1.0871 | 65.5766 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3