metadata
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Tiny ID - FLEURS-CV
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: id_id
split: test
metrics:
- type: wer
value: 30.8
name: WER
- type: cer
value: 11.29
name: CER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0
type: mozilla-foundation/common_voice_11_0
config: id
split: test
metrics:
- type: wer
value: 32.49
name: WER
- type: cer
value: 12.25
name: CER
Whisper Tiny ID - FLEURS-CV
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5129
- Wer: 31.1298
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: 32
- eval_batch_size: 16
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.617 | 1.43 | 500 | 0.5956 | 40.1521 |
| 0.4062 | 2.86 | 1000 | 0.4991 | 33.2066 |
| 0.2467 | 4.29 | 1500 | 0.4755 | 31.6802 |
| 0.1904 | 5.71 | 2000 | 0.4681 | 30.5907 |
| 0.118 | 7.14 | 2500 | 0.4776 | 30.9368 |
| 0.0941 | 8.57 | 3000 | 0.4831 | 30.7297 |
| 0.0771 | 10.0 | 3500 | 0.4912 | 31.1014 |
| 0.0536 | 11.43 | 4000 | 0.5043 | 31.2319 |
| 0.0502 | 12.86 | 4500 | 0.5113 | 31.2404 |
| 0.0418 | 14.29 | 5000 | 0.5129 | 31.1298 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2