metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- afrispeech-200
metrics:
- wer
model-index:
- name: whisper-small-hi-2400_500_100
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: afrispeech-200
type: afrispeech-200
config: all
split: train
args: all
metrics:
- name: Wer
type: wer
value: 0.6376484560570072
whisper-small-hi-2400_500_100
This model is a fine-tuned version of openai/whisper-small on the afrispeech-200 dataset. It achieves the following results on the evaluation set:
- Loss: 1.1136
- Wer: 0.6376
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 900
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.0658 | 0.17 | 150 | 2.3108 | 1.0536 |
| 1.4738 | 0.33 | 300 | 1.3138 | 1.0395 |
| 0.8823 | 1.17 | 450 | 1.2148 | 0.7992 |
| 1.1971 | 1.33 | 600 | 1.1466 | 0.7340 |
| 0.7529 | 2.17 | 750 | 1.1256 | 0.6723 |
| 1.1194 | 2.33 | 900 | 1.1136 | 0.6376 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2