metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: openai/whisper-tiny
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: eu
split: test
args: eu
metrics:
- name: Wer
type: wer
value: 33.15849163595123
openai/whisper-tiny
This model is a fine-tuned version of openai/whisper-tiny on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7321
- Wer: 33.1585
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: 3.75e-05
- train_batch_size: 256
- eval_batch_size: 128
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0096 | 19.0 | 1000 | 0.5796 | 32.8952 |
| 0.0011 | 38.0 | 2000 | 0.6522 | 32.2694 |
| 0.0005 | 57.01 | 3000 | 0.6949 | 33.1403 |
| 0.0003 | 76.01 | 4000 | 0.7217 | 33.0734 |
| 0.0003 | 96.0 | 5000 | 0.7321 | 33.1585 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3