--- language: - he base_model: ivrit-ai/whisper-v2-pd1-e1 tags: - hf-asr-leaderboard - generated_from_trainer metrics: - wer model-index: - name: he-cantillation results: [] --- # he-cantillation This model is a fine-tuned version of [ivrit-ai/whisper-v2-pd1-e1](https://huggingface.co/ivrit-ai/whisper-v2-pd1-e1) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1065 - Wer: 11.5595 - Avg Precision Exact: 0.9158 - Avg Recall Exact: 0.9153 - Avg F1 Exact: 0.9152 - Avg Precision Letter Shift: 0.9349 - Avg Recall Letter Shift: 0.9345 - Avg F1 Letter Shift: 0.9344 - Avg Precision Word Level: 0.9374 - Avg Recall Word Level: 0.9371 - Avg F1 Word Level: 0.9369 - Avg Precision Word Shift: 0.9744 - Avg Recall Word Shift: 0.9751 - Avg F1 Word Shift: 0.9743 - Precision Median Exact: 1.0 - Recall Median Exact: 1.0 - F1 Median Exact: 1.0 - Precision Max Exact: 1.0 - Recall Max Exact: 1.0 - F1 Max Exact: 1.0 - Precision Min Exact: 0.0 - Recall Min Exact: 0.0 - F1 Min Exact: 0.0 - Precision Min Letter Shift: 0.0 - Recall Min Letter Shift: 0.0 - F1 Min Letter Shift: 0.0 - Precision Min Word Level: 0.0 - Recall Min Word Level: 0.0 - F1 Min Word Level: 0.0 - Precision Min Word Shift: 0.2222 - Recall Min Word Shift: 0.1667 - F1 Min Word Shift: 0.1905 ## 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: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - training_steps: 10000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Avg Precision Exact | Avg Recall Exact | Avg F1 Exact | Avg Precision Letter Shift | Avg Recall Letter Shift | Avg F1 Letter Shift | Avg Precision Word Level | Avg Recall Word Level | Avg F1 Word Level | Avg Precision Word Shift | Avg Recall Word Shift | Avg F1 Word Shift | Precision Median Exact | Recall Median Exact | F1 Median Exact | Precision Max Exact | Recall Max Exact | F1 Max Exact | Precision Min Exact | Recall Min Exact | F1 Min Exact | Precision Min Letter Shift | Recall Min Letter Shift | F1 Min Letter Shift | Precision Min Word Level | Recall Min Word Level | F1 Min Word Level | Precision Min Word Shift | Recall Min Word Shift | F1 Min Word Shift | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:| | No log | 8e-05 | 1 | 4.8435 | 119.6859 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | | 0.1248 | 0.08 | 1000 | 0.1621 | 23.2816 | 0.8165 | 0.8201 | 0.8175 | 0.8444 | 0.8482 | 0.8454 | 0.8487 | 0.8532 | 0.8501 | 0.9200 | 0.9275 | 0.9227 | 0.9 | 0.9 | 0.8966 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1111 | 0.0909 | 0.1111 | | 0.0907 | 0.16 | 2000 | 0.1268 | 18.2188 | 0.8624 | 0.8589 | 0.8600 | 0.8863 | 0.8828 | 0.8839 | 0.8905 | 0.8869 | 0.8880 | 0.9507 | 0.9495 | 0.9494 | 0.9231 | 0.9167 | 0.9231 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.125 | 0.1333 | | 0.04 | 0.24 | 3000 | 0.1182 | 14.9446 | 0.8826 | 0.8813 | 0.8815 | 0.9046 | 0.9035 | 0.9035 | 0.9079 | 0.9067 | 0.9068 | 0.9633 | 0.9635 | 0.9628 | 0.9375 | 0.9375 | 0.9524 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.125 | 0.1 | 0.1176 | | 0.0379 | 0.32 | 4000 | 0.1123 | 15.0111 | 0.8839 | 0.8853 | 0.8839 | 0.9081 | 0.9096 | 0.9082 | 0.9110 | 0.9134 | 0.9115 | 0.9615 | 0.9658 | 0.9629 | 0.9333 | 0.9333 | 0.9474 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1 | 0.1 | 0.1176 | | 0.0274 | 0.4 | 5000 | 0.1092 | 13.3481 | 0.9011 | 0.8989 | 0.8996 | 0.9215 | 0.9194 | 0.9200 | 0.9240 | 0.9225 | 0.9228 | 0.9684 | 0.9685 | 0.9679 | 1.0 | 1.0 | 0.9630 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.1 | 0.1176 | | 0.0242 | 0.48 | 6000 | 0.1078 | 13.0044 | 0.9003 | 0.8977 | 0.8985 | 0.9211 | 0.9187 | 0.9194 | 0.9237 | 0.9216 | 0.9221 | 0.9686 | 0.9681 | 0.9678 | 1.0 | 1.0 | 0.9630 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.1 | 0.1176 | | 0.0134 | 0.56 | 7000 | 0.1039 | 12.0547 | 0.9086 | 0.9072 | 0.9075 | 0.9270 | 0.9257 | 0.9259 | 0.9299 | 0.9288 | 0.9290 | 0.9699 | 0.9701 | 0.9696 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1538 | 0.1429 | 0.1538 | | 0.0118 | 0.64 | 8000 | 0.1077 | 11.8847 | 0.9104 | 0.9110 | 0.9103 | 0.9306 | 0.9313 | 0.9306 | 0.9331 | 0.9339 | 0.9331 | 0.9726 | 0.9748 | 0.9733 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0769 | 0.0909 | 0.0833 | | 0.0084 | 0.72 | 9000 | 0.1071 | 11.6223 | 0.9145 | 0.9141 | 0.9140 | 0.9336 | 0.9332 | 0.9330 | 0.9358 | 0.9355 | 0.9353 | 0.9742 | 0.9751 | 0.9742 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.1 | 0.1176 | | 0.0065 | 0.8 | 10000 | 0.1065 | 11.5595 | 0.9158 | 0.9153 | 0.9152 | 0.9349 | 0.9345 | 0.9344 | 0.9374 | 0.9371 | 0.9369 | 0.9744 | 0.9751 | 0.9743 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2222 | 0.1667 | 0.1905 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.2.1 - Datasets 2.20.0 - Tokenizers 0.19.1