README.md

---
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