metadata
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-medium-common_voice_17_0-id-10000
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_17_0 id
type: mozilla-foundation/common_voice_17_0
config: id
split: None
args: id
metrics:
- name: Wer
type: wer
value: 0.04241496125110214
whisper-medium-common_voice_17_0-id-10000
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_17_0 id dataset. It achieves the following results on the evaluation set:
- Loss: 0.0574
- Wer: 0.0424
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.132 | 0.8457 | 1000 | 0.0963 | 0.0747 |
| 0.0503 | 1.6913 | 2000 | 0.0664 | 0.0526 |
| 0.023 | 2.5370 | 3000 | 0.0628 | 0.0727 |
| 0.011 | 3.3827 | 4000 | 0.0593 | 0.0437 |
| 0.0033 | 4.2283 | 5000 | 0.0575 | 0.0407 |
| 0.0017 | 5.0740 | 6000 | 0.0574 | 0.0448 |
| 0.0013 | 5.9197 | 7000 | 0.0554 | 0.0386 |
| 0.002 | 6.7653 | 8000 | 0.0555 | 0.0426 |
| 0.0002 | 7.6110 | 9000 | 0.0571 | 0.0421 |
| 0.0005 | 8.4567 | 10000 | 0.0574 | 0.0424 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1