metadata
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- librispeech_asr
metrics:
- wer
model-index:
- name: Whisper Tiny LibriSpeech
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: LibriSpeech Clean
type: librispeech_asr
args: 'config: clean, split: test'
metrics:
- name: Wer
type: wer
value: 98.61533779671333
Whisper Tiny LibriSpeech
This model is a fine-tuned version of openai/whisper-tiny on the LibriSpeech Clean dataset. It achieves the following results on the evaluation set:
- Loss: 1.0786
- Wer: 98.6153
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: 16
- eval_batch_size: 8
- seed: 42
- 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: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.0289 | 0.0561 | 100 | 1.0786 | 98.6153 |
Framework versions
- Transformers 5.5.3
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.22.2