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Teamim-AllNusah-whisper-medium_Warmup_steps-1000_LR-1e-05_Random-True
cantillation/Teamim-AllNusah-whisper-medium_Warmup_steps-1000_LR-1e-05_Random-True
Teamim-AllNusah-whisper-medium_Warmup_steps-1000_LR-1e-05_Random-True is a automatic speech recognition model from cantillation. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Mar 15, 2024
- Updated
- Mar 16, 2024
- SHA
- 6d7668ba
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
he-cantillation
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.1666
- eval_wer: 10.9128
- eval_avg_precision_Exact: 0.9184
- eval_avg_recall_Exact: 0.9197
- eval_avg_f1_Exact: 0.9188
- eval_avg_precision_Letter_Shift: 0.9365
- eval_avg_recall_Letter_Shift: 0.9379
- eval_avg_f1_Letter_Shift: 0.9369
- eval_avg_precision_Word_Level: 0.9382
- eval_avg_recall_Word_Level: 0.9395
- eval_avg_f1_Word_Level: 0.9385
- eval_avg_precision_Word_Shift: 0.9779
- eval_avg_recall_Word_Shift: 0.9797
- eval_avg_f1_Word_Shift: 0.9784
- eval_precision_median_exact: 1.0
- eval_recall_median_exact: 1.0
- eval_f1_median_exact: 1.0
- eval_precision_max_exact: 1.0
- eval_recall_max_exact: 1.0
- eval_f1_max_exact: 1.0
- eval_precision_min_Exact: 0.0
- eval_recall_min_Exact: 0.0
- eval_f1_min_Exact: 0.0
- eval_precision_min_Letter_Shift: 0.0
- eval_recall_min_Letter_Shift: 0.0
- eval_f1_min_Letter_Shift: 0.0
- eval_precision_min_Word_Level: 0.0
- eval_recall_min_Word_Level: 0.0
- eval_f1_min_Word_Level: 0.0
- eval_precision_min_Word_Shift: 0.1429
- eval_recall_min_Word_Shift: 0.1111
- eval_f1_min_Word_Shift: 0.125
- eval_runtime: 1554.5785
- eval_samples_per_second: 1.732
- eval_steps_per_second: 0.055
- epoch: 4.0
- step: 50000
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: 1000
- training_steps: 50000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- he
- Created
- Mar 15, 2024
- Updated
- Mar 16, 2024