metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: output_dir
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: rw
split: test
args: rw
metrics:
- name: Wer
type: wer
value: 43.75236083594792
output_dir
This model is a fine-tuned version of openai/whisper-small on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6424
- Wer: 43.7524
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: 20
- eval_batch_size: 20
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 40
- total_eval_batch_size: 40
- 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 |
|---|---|---|---|---|
| 0.7471 | 0.04 | 1000 | 0.9044 | 59.2903 |
| 0.5987 | 0.08 | 2000 | 0.7523 | 52.0232 |
| 0.5168 | 0.12 | 3000 | 0.6890 | 47.7610 |
| 0.5082 | 0.16 | 4000 | 0.6596 | 45.4013 |
| 0.4748 | 0.2 | 5000 | 0.6424 | 43.7524 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2