---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- razhan/common_voice_ckb_16
metrics:
- wer
model-index:
- name: whisper-base-ckb
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: razhan/common_voice_ckb_16
      type: razhan/common_voice_ckb_16
    metrics:
    - name: Wer
      type: wer
      value: 0.12623194275685162
---

<!-- 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-base-ckb

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the razhan/common_voice_ckb_16 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0641
- Wer: 0.1262

## 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: 192
- eval_batch_size: 128
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- total_train_batch_size: 1152
- total_eval_batch_size: 768
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2300
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3434        | 1.09  | 100  | 0.3840          | 0.6054 |
| 0.2089        | 2.17  | 200  | 0.2654          | 0.4740 |
| 0.167         | 3.26  | 300  | 0.2246          | 0.4190 |
| 0.1452        | 4.35  | 400  | 0.1964          | 0.3803 |
| 0.1287        | 5.43  | 500  | 0.1788          | 0.3542 |
| 0.1163        | 6.52  | 600  | 0.1650          | 0.3326 |
| 0.1068        | 7.61  | 700  | 0.1560          | 0.3155 |
| 0.1015        | 8.7   | 800  | 0.1489          | 0.3059 |
| 0.0968        | 9.78  | 900  | 0.1440          | 0.2954 |
| 0.0939        | 10.87 | 1000 | 0.1420          | 0.2918 |
| 0.0919        | 11.96 | 1100 | 0.1315          | 0.2742 |
| 0.0839        | 13.04 | 1200 | 0.1217          | 0.2597 |
| 0.0713        | 14.13 | 1300 | 0.1132          | 0.2371 |
| 0.0687        | 15.22 | 1400 | 0.1091          | 0.2372 |
| 0.0647        | 16.3  | 1500 | 0.1022          | 0.2173 |
| 0.059         | 17.39 | 1600 | 0.0967          | 0.2043 |
| 0.0539        | 18.48 | 1700 | 0.0897          | 0.1929 |
| 0.0518        | 19.57 | 1800 | 0.0827          | 0.1718 |
| 0.0495        | 20.65 | 1900 | 0.0787          | 0.1667 |
| 0.0444        | 21.74 | 2000 | 0.0718          | 0.1469 |
| 0.0392        | 22.83 | 2100 | 0.0671          | 0.1368 |
| 0.0335        | 23.91 | 2200 | 0.0645          | 0.1263 |
| 0.0292        | 25.0  | 2300 | 0.0641          | 0.1262 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0