metadata
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-tiny-ft-cy
results: []
license: apache-2.0
language:
- cy
- en
pipeline_tag: automatic-speech-recognition
whisper-tiny-ft-cy-en
This model is a fine-tune of openai/whisper-tiny using custom splits from Common Voice 16.1 Welsh and English datasets as well as normalized verbatim transcriptions from techiaith/banc-trawsgrifiadau-bangor
Intended uses & limitations
Due to its small size, this model is intended to be used as the basis for offline speech recognition on devices such as Android phones.
Training and evaluation data
It achieves the following results on the evaluation set:
- Loss: 0.7176
- Wer: 53.1135
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8115 | 1.41 | 1000 | 0.8426 | 60.0795 |
| 0.6396 | 2.83 | 2000 | 0.7508 | 54.4259 |
| 0.5259 | 4.24 | 3000 | 0.7255 | 53.1328 |
| 0.4854 | 5.66 | 4000 | 0.7176 | 53.1135 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1