metadata
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
base_model: openai/whisper-base
model-index:
- name: Whisper Tiny Pashto
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs ps_af
type: google/fleurs
config: ps_af
split: test
args: ps_af
metrics:
- type: wer
value: 69.61259079903148
name: Wer
Whisper Tiny Pashto
This model is a fine-tuned version of openai/whisper-base on the google/fleurs ps_af dataset. It achieves the following results on the evaluation set:
- Loss: 1.0742
- Wer: 69.6126
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: 16
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.8225 | 14.29 | 100 | 1.7608 | 105.3193 |
| 0.7281 | 28.57 | 200 | 1.0742 | 69.6126 |
| 0.2329 | 42.86 | 300 | 1.1192 | 67.0248 |
| 0.0247 | 57.14 | 400 | 1.3495 | 66.3741 |
| 0.0057 | 71.43 | 500 | 1.5055 | 67.2896 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2