--- license: apache-2.0 tags: - generated_from_trainer datasets: - fleurs metrics: - wer model-index: - name: whisper-large-v2-greek results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: fleurs type: fleurs config: el_gr split: test args: el_gr metrics: - name: Wer type: wer value: 1.0564819086535293 --- # whisper-large-v2-greek This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the fleurs dataset. It achieves the following results on the evaluation set: - Loss: 0.2061 - Wer Ortho: 1.0424 - Wer: 1.0565 ## 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: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant_with_warmup - lr_scheduler_warmup_steps: 50 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| | 0.1416 | 1.0 | 217 | 0.1611 | 1.2560 | 1.2638 | | 0.0617 | 2.0 | 435 | 0.1612 | 1.1956 | 1.1930 | | 0.027 | 3.0 | 653 | 0.1716 | 1.6495 | 1.6518 | | 0.0155 | 4.0 | 871 | 0.1812 | 1.2816 | 1.2878 | | 0.0114 | 5.0 | 1088 | 0.1792 | 1.0087 | 1.0071 | | 0.0085 | 6.0 | 1306 | 0.1891 | 0.9757 | 0.9971 | | 0.0073 | 7.0 | 1524 | 0.2017 | 1.0040 | 1.0225 | | 0.0062 | 8.0 | 1742 | 0.1980 | 1.0737 | 1.0779 | | 0.0094 | 9.0 | 1959 | 0.2103 | 0.8469 | 0.8459 | | 0.0039 | 9.97 | 2170 | 0.2061 | 1.0424 | 1.0565 | ### Framework versions - Transformers 4.30.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3