metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: openai/whisper-tiny
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: it
split: test
args: it
metrics:
- name: Wer
type: wer
value: 26.495056347012547
openai/whisper-tiny
This model is a fine-tuned version of openai/whisper-tiny on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4736
- Wer: 26.4951
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3889 | 0.2 | 1000 | 0.6844 | 39.1000 |
| 0.5832 | 0.4 | 2000 | 0.5691 | 31.9995 |
| 0.524 | 0.6 | 3000 | 0.4993 | 28.2672 |
| 0.4663 | 0.8 | 4000 | 0.4799 | 26.7230 |
| 0.3107 | 1.05 | 5000 | 0.4736 | 26.4951 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2