--- 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: 0.0811 - Wer: 8.3294 - Avg Precision Exact: 0.9316 - Avg Recall Exact: 0.9306 - Avg F1 Exact: 0.9308 - Avg Precision Letter Shift: 0.9429 - Avg Recall Letter Shift: 0.9420 - Avg F1 Letter Shift: 0.9421 - Avg Precision Word Level: 0.9449 - Avg Recall Word Level: 0.9440 - Avg F1 Word Level: 0.9441 - Avg Precision Word Shift: 0.9733 - Avg Recall Word Shift: 0.9727 - Avg F1 Word Shift: 0.9726 - 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: 0.1429 - Recall Min Word Shift: 0.125 - F1 Min Word Shift: 0.1333 ## 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: 30000 - 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 | 0.0001 | 1 | 5.0569 | 117.7539 | 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 | | 0.0574 | 0.2584 | 5000 | 0.1118 | 15.1956 | 0.8739 | 0.8737 | 0.8732 | 0.8937 | 0.8935 | 0.8931 | 0.8968 | 0.8969 | 0.8963 | 0.9461 | 0.9483 | 0.9466 | 0.9286 | 0.9231 | 0.9333 | 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 | | 0.0305 | 0.5167 | 10000 | 0.0953 | 11.9985 | 0.8991 | 0.8996 | 0.8989 | 0.9138 | 0.9146 | 0.9137 | 0.9165 | 0.9178 | 0.9167 | 0.9563 | 0.9591 | 0.9571 | 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 | 0.125 | 0.1333 | | 0.0185 | 0.7751 | 15000 | 0.0868 | 10.8122 | 0.9110 | 0.9117 | 0.9110 | 0.9265 | 0.9273 | 0.9265 | 0.9291 | 0.9301 | 0.9291 | 0.9629 | 0.9645 | 0.9632 | 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 | 0.125 | 0.1333 | | 0.0126 | 1.0334 | 20000 | 0.0848 | 9.5283 | 0.9168 | 0.9163 | 0.9162 | 0.9298 | 0.9294 | 0.9292 | 0.9321 | 0.9316 | 0.9315 | 0.9672 | 0.9670 | 0.9666 | 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 | 0.125 | 0.1333 | | 0.0061 | 1.2918 | 25000 | 0.0850 | 8.8801 | 0.9244 | 0.9266 | 0.9251 | 0.9358 | 0.9381 | 0.9366 | 0.9381 | 0.9403 | 0.9388 | 0.9686 | 0.9706 | 0.9691 | 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 | 0.125 | 0.1333 | | 0.0069 | 1.5501 | 30000 | 0.0811 | 8.3294 | 0.9316 | 0.9306 | 0.9308 | 0.9429 | 0.9420 | 0.9421 | 0.9449 | 0.9440 | 0.9441 | 0.9733 | 0.9727 | 0.9726 | 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 | 0.125 | 0.1333 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.2.1 - Datasets 2.20.0 - Tokenizers 0.19.1