metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- common_voice_16_0
metrics:
- wer
model-index:
- name: breeze-dsw-tiny-ml
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_16_0
type: common_voice_16_0
config: ml
split: test
args: ml
metrics:
- name: Wer
type: wer
value: 55.097312326227986
breeze-dsw-tiny-ml
This model is a fine-tuned version of openai/whisper-tiny on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7383
- Wer: 55.0973
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: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.1736 | 2.02 | 100 | 1.1670 | 99.7776 |
| 0.9647 | 4.04 | 200 | 1.0049 | 95.4866 |
| 0.5311 | 7.02 | 300 | 0.6807 | 74.5598 |
| 0.3036 | 9.04 | 400 | 0.5410 | 61.5755 |
| 0.1672 | 12.02 | 500 | 0.5146 | 56.5709 |
| 0.1006 | 14.04 | 600 | 0.5503 | 54.3744 |
| 0.0484 | 17.02 | 700 | 0.5859 | 54.5042 |
| 0.0305 | 19.04 | 800 | 0.6562 | 55.4124 |
| 0.0147 | 22.02 | 900 | 0.7095 | 54.8749 |
| 0.0116 | 24.04 | 1000 | 0.7383 | 55.0973 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0