|
--- |
|
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 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# whisper-tiny-ft-cy-en |
|
|
|
This model is a fine-tune of [openai/whisper-tiny](https://huggingface.co/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](https://huggingface.co/datasets/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 |
