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---
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 |