metadata
language:
- uk
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small uk
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: uk
split: test
args: uk
metrics:
- name: Wer
type: wer
value: 18.286614695637752
Whisper Small uk
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4347
- Wer: 18.2866
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: 64
- eval_batch_size: 8
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1881 | 1.8182 | 1000 | 0.2974 | 19.3302 |
| 0.0651 | 3.6364 | 2000 | 0.3102 | 18.6128 |
| 0.018 | 5.4545 | 3000 | 0.3674 | 18.3848 |
| 0.0049 | 7.2727 | 4000 | 0.4165 | 18.6087 |
| 0.0035 | 9.0909 | 5000 | 0.4347 | 18.2866 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1