metadata
library_name: peft
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small English (1000 steps) - Jarrett Er
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: en
split: train
args: 'config: en, split: train'
metrics:
- type: wer
value: 10.99832565927166
name: Wer
Whisper Small English (1000 steps) - Jarrett Er
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2214
- Wer: 10.9983
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2461 | 0.1 | 100 | 0.2450 | 11.8146 |
| 0.2253 | 0.2 | 200 | 0.2343 | 11.2599 |
| 0.2663 | 0.3 | 300 | 0.2287 | 11.2495 |
| 0.252 | 0.4 | 400 | 0.2241 | 11.0506 |
| 0.2301 | 0.5 | 500 | 0.2245 | 11.4064 |
| 0.1985 | 1.037 | 600 | 0.2208 | 11.0297 |
| 0.1768 | 1.137 | 700 | 0.2230 | 11.2181 |
| 0.1107 | 1.237 | 800 | 0.2226 | 11.0820 |
| 0.0819 | 1.337 | 900 | 0.2228 | 11.1134 |
| 0.185 | 1.437 | 1000 | 0.2214 | 10.9983 |
Framework versions
- PEFT 0.14.0
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.1.dev0
- Tokenizers 0.21.0