--- language: - he license: apache-2.0 base_model: openai/whisper-large-v2 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 [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1029 - Wer: 11.7332 - Avg Precision Exact: 0.9091 - Avg Recall Exact: 0.9078 - Avg F1 Exact: 0.9081 - Avg Precision Letter Shift: 0.9280 - Avg Recall Letter Shift: 0.9269 - Avg F1 Letter Shift: 0.9271 - Avg Precision Word Level: 0.9303 - Avg Recall Word Level: 0.9294 - Avg F1 Word Level: 0.9295 - Avg Precision Word Shift: 0.9756 - Avg Recall Word Shift: 0.9759 - Avg F1 Word Shift: 0.9754 - 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: 0.1 - F1 Min Word Shift: 0.1176 ## 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: 8000 - 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 | 5.7968 | 117.0732 | 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 | | 0.1322 | 0.08 | 1000 | 0.1679 | 24.1907 | 0.8065 | 0.8169 | 0.8107 | 0.8367 | 0.8476 | 0.8410 | 0.8414 | 0.8525 | 0.8458 | 0.9193 | 0.9337 | 0.9252 | 0.8889 | 0.9 | 0.8889 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | | 0.0895 | 0.16 | 2000 | 0.1293 | 17.7679 | 0.8618 | 0.8637 | 0.8621 | 0.8863 | 0.8883 | 0.8867 | 0.8902 | 0.8927 | 0.8908 | 0.9500 | 0.9551 | 0.9518 | 0.9231 | 0.9231 | 0.9286 | 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 | 0.1111 | 0.125 | | 0.0448 | 0.24 | 3000 | 0.1182 | 15.4065 | 0.8816 | 0.8881 | 0.8843 | 0.9059 | 0.9128 | 0.9088 | 0.9087 | 0.9156 | 0.9116 | 0.9607 | 0.9675 | 0.9635 | 0.9310 | 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 | 0.1429 | 0.125 | 0.1333 | | 0.0341 | 0.32 | 4000 | 0.1153 | 14.7894 | 0.8871 | 0.8897 | 0.8879 | 0.9110 | 0.9137 | 0.9118 | 0.9137 | 0.9170 | 0.9148 | 0.9646 | 0.9692 | 0.9663 | 0.9375 | 0.9444 | 0.9565 | 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 | 0.1111 | 0.125 | | 0.022 | 0.4 | 5000 | 0.1076 | 13.5772 | 0.8993 | 0.8954 | 0.8969 | 0.9224 | 0.9185 | 0.9199 | 0.9251 | 0.9216 | 0.9229 | 0.9710 | 0.9696 | 0.9698 | 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 | 0.0833 | 0.1053 | | 0.0172 | 0.48 | 6000 | 0.1037 | 12.3245 | 0.9086 | 0.9078 | 0.9078 | 0.9283 | 0.9277 | 0.9276 | 0.9306 | 0.9302 | 0.9300 | 0.9727 | 0.9740 | 0.9729 | 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 | 0.0769 | 0.0769 | | 0.0094 | 0.56 | 7000 | 0.1045 | 12.0806 | 0.9059 | 0.9058 | 0.9054 | 0.9257 | 0.9257 | 0.9253 | 0.9279 | 0.9280 | 0.9275 | 0.9733 | 0.9747 | 0.9735 | 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 | | 0.014 | 0.64 | 8000 | 0.1029 | 11.7332 | 0.9091 | 0.9078 | 0.9081 | 0.9280 | 0.9269 | 0.9271 | 0.9303 | 0.9294 | 0.9295 | 0.9756 | 0.9759 | 0.9754 | 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 | ### Framework versions - Transformers 4.42.0.dev0 - Pytorch 1.13.1+cu117 - Datasets 2.16.1 - Tokenizers 0.19.1