metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- razhan/common_voice_ckb_16
metrics:
- wer
model-index:
- name: whisper-tiny-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: 0.47801004237740824
whisper-tiny-ckb
This model is a fine-tuned version of openai/whisper-tiny on the razhan/common_voice_ckb_16 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2612
- Wer: 0.4780
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: 4
- total_train_batch_size: 768
- total_eval_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 600
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4502 | 0.72 | 100 | 0.4988 | 0.7166 |
| 0.2977 | 1.45 | 200 | 0.3557 | 0.5859 |
| 0.2494 | 2.17 | 300 | 0.3096 | 0.5315 |
| 0.2224 | 2.9 | 400 | 0.2817 | 0.5008 |
| 0.2148 | 3.62 | 500 | 0.2666 | 0.4819 |
| 0.2096 | 4.35 | 600 | 0.2612 | 0.4780 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0