--- language: - he license: apache-2.0 base_model: openai/whisper-medium tags: - hf-asr-leaderboard - generated_from_trainer metrics: - precision - recall - f1 model-index: - name: he results: [] --- # he This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0736 - Precision: 0.4148 - Recall: 0.4107 - F1: 0.4125 - Precision Median: 0.0 - Recall Median: 0.0 - F1 Median: 0.0 - Precision Max: 1.0 - Recall Max: 1.0 - F1 Max: 1.0 - Precision Min: 0.0 - Recall Min: 0.0 - F1 Min: 0.0 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Precision Median | Recall Median | F1 Median | Precision Max | Recall Max | F1 Max | Precision Min | Recall Min | F1 Min | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:----------------:|:-------------:|:---------:|:-------------:|:----------:|:------:|:-------------:|:----------:|:------:| | 0.0445 | 0.4 | 1000 | 0.0839 | 0.2598 | 0.2539 | 0.2566 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | | 0.0203 | 0.79 | 2000 | 0.0686 | 0.5017 | 0.4976 | 0.4993 | 0.6667 | 0.6667 | 0.6667 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | | 0.013 | 1.19 | 3000 | 0.0723 | 0.3647 | 0.3629 | 0.3635 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | | 0.0016 | 1.58 | 4000 | 0.0736 | 0.4148 | 0.4107 | 0.4125 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | ### Framework versions - Transformers 4.36.2 - Pytorch 1.13.1+cu117 - Datasets 2.16.1 - Tokenizers 0.15.0