metadata
library_name: transformers
language:
- ug
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small ug - Sanchit Gandhi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11
type: mozilla-foundation/common_voice_11_0
config: ug
split: test
args: ug
metrics:
- name: Wer
type: wer
value: 34.25947275382369
Whisper Small ug - Sanchit Gandhi
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3966
- Wer Ortho: 39.5518
- Wer: 34.2595
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0842 | 3.9216 | 1000 | 0.2856 | 44.0534 | 37.9371 |
| 0.0173 | 7.8431 | 2000 | 0.3364 | 40.8646 | 34.9089 |
| 0.0087 | 11.7647 | 3000 | 0.3656 | 39.9169 | 34.3824 |
| 0.0065 | 15.6863 | 4000 | 0.3966 | 39.5518 | 34.2595 |
| 0.0068 | 19.6078 | 5000 | 0.3997 | 39.5790 | 34.3210 |
Framework versions
- Transformers 4.45.2
- Pytorch 1.12.0+cu113
- Datasets 3.0.2
- Tokenizers 0.20.1