metadata
library_name: transformers
language:
- tw
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- fsicoli/common_voice_18_0
metrics:
- wer
model-index:
- name: Raydox11-whisper-small
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fsicoli/common_voice_18_0
type: fsicoli/common_voice_18_0
config: tw
split: None
args: 'config: tw, split: test'
metrics:
- name: Wer
type: wer
value: 85.39325842696628
Raydox11-whisper-small
This model is a fine-tuned version of openai/whisper-small on the fsicoli/common_voice_18_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.7598
- Wer: 85.3933
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: 8
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 700
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0003 | 83.3333 | 700 | 1.7598 | 85.3933 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1