metadata
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: >-
whisper-bs-cs-train-noaug-test-tstretch20-gain10-pitch20-gaussian20-lowpass10-mp3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: cs
split: None
args: cs
metrics:
- name: Wer
type: wer
value: 65.93546248204221
whisper-bs-cs-train-noaug-test-tstretch20-gain10-pitch20-gaussian20-lowpass10-mp3
This model is a fine-tuned version of openai/whisper-base on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0830
- Wer: 65.9355
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3007 | 1.4440 | 1000 | 1.1013 | 72.5808 |
| 0.1741 | 2.8881 | 2000 | 1.0371 | 69.6725 |
| 0.0972 | 4.3321 | 3000 | 1.0761 | 66.3609 |
| 0.079 | 5.7762 | 4000 | 1.0830 | 65.9355 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1