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