metadata
language:
- hi
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 tr - erenozaltun-common11
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: tr
split: None
args: 'config: tr, split: test'
metrics:
- name: Wer
type: wer
value: 20.694339329723853
Whisper Small tr - erenozaltun-common11
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2533
- Wer: 20.6943
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2185 | 0.4429 | 1000 | 0.2911 | 25.1363 |
| 0.1815 | 0.8857 | 2000 | 0.2704 | 23.0541 |
| 0.0852 | 1.3286 | 3000 | 0.2624 | 21.8296 |
| 0.0705 | 1.7715 | 4000 | 0.2520 | 20.7564 |
| 0.0431 | 2.2143 | 5000 | 0.2533 | 20.6943 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1