--- language: - el license: apache-2.0 tags: - whisper-event - generated_from_trainer - hf-asr-leaderboard - automatic-speech-recognition - greeek datasets: - mozilla-foundation/common_voice_11_0 - google/fleurs metrics: - wer model-index: - name: whisper-sm-el-intlv-xs results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_11_0 type: mozilla-foundation/common_voice_11_0 args: 'config: el, split: test' metrics: - name: Wer type: wer value: 20.068722139673106 --- # Whisper small (Greek) Trained on Interleaved Datasets This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr dataset. It achieves the following results on the evaluation set: - Loss: 0.4741 - Wer: 20.0687 ## 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 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0186 | 4.98 | 1000 | 0.3619 | 21.0067 | | 0.0012 | 9.95 | 2000 | 0.4347 | 20.3009 | | 0.0005 | 14.93 | 3000 | 0.4741 | 20.0687 | | 0.0003 | 19.9 | 4000 | 0.4974 | 20.1152 | | 0.0003 | 24.88 | 5000 | 0.5066 | 20.2266 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0 - Datasets 2.7.1.dev0 - Tokenizers 0.12.1