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---
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: 0.2917510463075469
---
<!-- 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: 0.1420
- Wer: 0.2918
## 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: 1000
- 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 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0
|