metadata
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- common_voice_16_0
metrics:
- wer
model-index:
- name: breeze-listen-dsw-base-id
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_16_0
type: common_voice_16_0
config: id
split: test
args: id
metrics:
- name: Wer
type: wer
value: 33.82555892906431
breeze-listen-dsw-base-id
This model is a fine-tuned version of openai/whisper-base on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6528
- Wer: 33.8256
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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5452 | 1.02 | 200 | 0.5464 | 35.1688 |
| 0.3445 | 2.04 | 400 | 0.5405 | 34.0694 |
| 0.1397 | 3.07 | 600 | 0.5347 | 32.8273 |
| 0.0988 | 5.01 | 800 | 0.5654 | 35.6749 |
| 0.077 | 6.03 | 1000 | 0.5786 | 33.9452 |
| 0.0338 | 7.05 | 1200 | 0.6050 | 33.9820 |
| 0.0137 | 8.08 | 1400 | 0.6221 | 34.1016 |
| 0.0153 | 10.02 | 1600 | 0.6431 | 33.9038 |
| 0.0125 | 11.04 | 1800 | 0.6514 | 33.7520 |
| 0.0092 | 12.06 | 2000 | 0.6528 | 33.8256 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0