metadata
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Tiny Pashto
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs ps_af
type: google/fleurs
config: ps_af
split: test
args: ps_af
metrics:
- name: Wer
type: wer
value: 60.05599273607748
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: 0.8714
- Wer: 60.0560
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-07
- 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: 100
- training_steps: 1300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.9153 | 2.5 | 100 | 1.0240 | 68.9864 |
| 0.6865 | 5.0 | 200 | 0.8968 | 61.7660 |
| 0.5474 | 7.5 | 300 | 0.8744 | 60.5554 |
| 0.4646 | 10.0 | 400 | 0.8710 | 60.0560 |
| 0.4557 | 12.5 | 500 | 0.8732 | 59.4658 |
| 0.3882 | 15.0 | 600 | 0.8819 | 59.0648 |
| 0.3346 | 17.5 | 700 | 0.9032 | 59.4809 |
| 0.2947 | 20.0 | 800 | 0.9144 | 59.7685 |
| 0.2724 | 22.5 | 900 | 0.9289 | 58.9815 |
| 0.2785 | 25.0 | 1000 | 0.9339 | 59.2010 |
| 0.2454 | 27.5 | 1100 | 0.9439 | 59.1934 |
| 0.2297 | 30.0 | 1200 | 0.9485 | 59.0421 |
| 0.2383 | 33.33 | 1300 | 0.9529 | 59.0799 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2