metadata
language:
- he
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-he
results: []
whisper-medium-he
This model is a fine-tuned version of openai/whisper-medium on the imvladikon/hebrew_speech_coursera dataset. It achieves the following results on the evaluation set:
- Loss: 0.2042
- Wer: 12.9071
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1865 | 0.1 | 1000 | 0.3587 | 21.4973 |
| 0.2601 | 0.2 | 2000 | 0.2673 | 17.1157 |
| 0.2033 | 0.3 | 3000 | 0.2238 | 14.4325 |
| 0.1988 | 0.39 | 4000 | 0.2042 | 12.9071 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0