metadata
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small 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: 63.10532687651331
Whisper Small Pashto
This model is a fine-tuned version of openai/whisper-small on the google/fleurs ps_af dataset. It achieves the following results on the evaluation set:
- Loss: 1.1800
- Wer: 63.1053
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: 3e-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: 10
- training_steps: 5200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.0871 | 14.29 | 100 | 2.0102 | 230.2739 |
| 1.465 | 28.57 | 200 | 1.4969 | 137.2427 |
| 1.1617 | 42.86 | 300 | 1.2716 | 76.3242 |
| 1.0019 | 57.14 | 400 | 1.1645 | 71.3756 |
| 0.9052 | 71.43 | 500 | 1.1051 | 69.7866 |
| 0.8334 | 85.71 | 600 | 1.0691 | 68.2657 |
| 0.7838 | 100.0 | 700 | 1.0483 | 67.1686 |
| 0.7539 | 114.29 | 800 | 1.0363 | 66.4195 |
| 0.7377 | 128.57 | 900 | 1.0297 | 66.2001 |
| 0.7325 | 142.86 | 1000 | 1.0277 | 66.0033 |
| 0.6952 | 157.14 | 1100 | 1.0122 | 65.0575 |
| 0.6531 | 171.43 | 1200 | 1.0014 | 64.4219 |
| 0.6189 | 185.71 | 1300 | 0.9945 | 63.7939 |
| 0.5993 | 200.0 | 1400 | 0.9896 | 63.3550 |
| 0.5757 | 214.29 | 1500 | 0.9864 | 63.2264 |
| 0.5601 | 228.57 | 1600 | 0.9845 | 62.9162 |
| 0.5482 | 242.86 | 1700 | 0.9833 | 62.8178 |
| 0.5382 | 257.14 | 1800 | 0.9827 | 62.8405 |
| 0.5325 | 271.43 | 1900 | 0.9823 | 62.7648 |
| 0.5287 | 285.71 | 2000 | 0.9822 | 62.8178 |
| 0.3494 | 357.14 | 2500 | 1.0026 | 61.6147 |
| 0.2287 | 428.57 | 3000 | 1.0533 | 61.5163 |
| 0.1525 | 500.0 | 3500 | 1.1041 | 62.0536 |
| 0.1089 | 571.43 | 4000 | 1.1451 | 62.5076 |
| 0.0871 | 642.86 | 4500 | 1.1704 | 62.9313 |
| 0.0797 | 714.29 | 5000 | 1.1791 | 63.1659 |
| 0.0799 | 728.57 | 5100 | 1.1800 | 63.1053 |
| 0.0791 | 742.86 | 5200 | 1.1803 | 63.1129 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2