metadata
library_name: transformers
language:
- dv
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper tuny Dv - hipstor
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: alakxender/dhivehi-audio-kn
type: mozilla-foundation/common_voice_13_0
metrics:
- name: Wer
type: wer
value: 79.58392820722007
Whisper tuny Dv - hipstor
This model is a fine-tuned version of openai/whisper-tiny on the alakxender/dhivehi-audio-kn dataset. It achieves the following results on the evaluation set:
- Loss: 0.9464
- Wer Ortho: 125.5444
- Wer: 79.5839
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: 4
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 3.7040 | 2.3933 | 500 | 0.9464 | 125.5444 | 79.5839 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.6.1
- Tokenizers 0.22.2