---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- DewiBrynJones/banc-trawsgrifiadau-bangor-clean
metrics:
- wer
model-index:
- name: whisper-large-v3-ft-btb-cy
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: DewiBrynJones/banc-trawsgrifiadau-bangor-clean default
      type: DewiBrynJones/banc-trawsgrifiadau-bangor-clean
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.3064475414845421
---

<!-- 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-large-v3-ft-btb-cy

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the DewiBrynJones/banc-trawsgrifiadau-bangor-clean default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5776
- Wer: 0.3064

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.3674        | 1.1390 | 1000 | 0.4709          | 0.3416 |
| 0.2228        | 2.2779 | 2000 | 0.4358          | 0.3117 |
| 0.1266        | 3.4169 | 3000 | 0.4588          | 0.3070 |
| 0.0611        | 4.5558 | 4000 | 0.5140          | 0.3039 |
| 0.0245        | 5.6948 | 5000 | 0.5776          | 0.3064 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1