---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- DewiBrynJones/commonvoice_18_0_cy
metrics:
- wer
model-index:
- name: whisper-large-v3-ft-cv-cy-train-all-plus-other-with-excluded
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: DewiBrynJones/commonvoice_18_0_cy default
      type: DewiBrynJones/commonvoice_18_0_cy
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.1676010974591435
---

<!-- 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-cv-cy-train-all-plus-other-with-excluded

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the DewiBrynJones/commonvoice_18_0_cy default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3280
- Wer: 0.1676

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.1583        | 1.4144 | 1000 | 0.2562          | 0.2062 |
| 0.0675        | 2.8289 | 2000 | 0.2394          | 0.1849 |
| 0.0113        | 4.2433 | 3000 | 0.2729          | 0.1722 |
| 0.0036        | 5.6577 | 4000 | 0.3004          | 0.1705 |
| 0.0012        | 7.0721 | 5000 | 0.3280          | 0.1676 |


### Framework versions

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