metadata
language:
- ps
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Base Pashto - Augmented
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs
type: google/fleurs
config: ps_af
split: test
args: ps_af
metrics:
- name: Wer
type: wer
value: 57.611985472154956
Whisper Base Pashto - Augmented
This model is a fine-tuned version of openai/whisper-base on the google/fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.8723
- Wer: 57.6120
- Cer: 26.6468
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.9708 | 2.38 | 100 | 0.8821 | 64.0133 | 27.3253 |
| 0.7477 | 4.75 | 200 | 0.8062 | 59.9576 | 26.4079 |
| 0.6229 | 7.14 | 300 | 0.7855 | 58.3081 | 26.3193 |
| 0.4833 | 9.52 | 400 | 0.7870 | 57.5288 | 24.8855 |
| 0.4084 | 11.89 | 500 | 0.7980 | 56.5224 | 25.2214 |
| 0.3323 | 14.28 | 600 | 0.8201 | 56.6662 | 25.3317 |
| 0.283 | 16.66 | 700 | 0.8406 | 57.7406 | 26.8674 |
| 0.2598 | 19.05 | 800 | 0.8538 | 57.2866 | 26.0386 |
| 0.2235 | 21.42 | 900 | 0.8697 | 58.2703 | 26.6819 |
| 0.2202 | 23.8 | 1000 | 0.8723 | 57.6120 | 26.6468 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2