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Teamim-large-v2-pd1-e1_WeightDecay-0.05_Augmented_Combined-Data_date-14-07-2024_18-24

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Hebrew
whisper
hf-asr-leaderboard
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
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  1. README.md +99 -0
  2. generation_config.json +316 -0
  3. model-00001-of-00002.safetensors +3 -0
  4. model-00002-of-00002.safetensors +3 -0
  5. model.safetensors.index.json +0 -0
  6. runs/Jul14_18-32-10_7cdaf268d1a8/events.out.tfevents.1720981932.7cdaf268d1a8.1.0 +2 -2
README.md ADDED
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+ ---
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+ base_model: ivrit-ai/whisper-v2-pd1-e1
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Teamim-large-v2_WeightDecay-0.05_Augmented_Combined-Data_date-14-07-2024_18-24
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Teamim-large-v2_WeightDecay-0.05_Augmented_Combined-Data_date-14-07-2024_18-24
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+
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+ 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.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0952
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+ - Wer: 7.8511
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+ - Avg Precision Exact: 0.9335
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+ - Avg Recall Exact: 0.9352
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+ - Avg F1 Exact: 0.9340
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+ - Avg Precision Letter Shift: 0.9440
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+ - Avg Recall Letter Shift: 0.9458
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+ - Avg F1 Letter Shift: 0.9446
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+ - Avg Precision Word Level: 0.9462
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+ - Avg Recall Word Level: 0.9479
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+ - Avg F1 Word Level: 0.9467
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+ - Avg Precision Word Shift: 0.9714
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+ - Avg Recall Word Shift: 0.9736
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+ - Avg F1 Word Shift: 0.9721
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+ - Precision Median Exact: 1.0
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+ - Recall Median Exact: 1.0
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+ - F1 Median Exact: 1.0
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+ - Precision Max Exact: 1.0
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+ - Recall Max Exact: 1.0
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+ - F1 Max Exact: 1.0
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+ - Precision Min Exact: 0.0
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+ - Recall Min Exact: 0.0
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+ - F1 Min Exact: 0.0
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+ - Precision Min Letter Shift: 0.0
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+ - Recall Min Letter Shift: 0.0
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+ - F1 Min Letter Shift: 0.0
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+ - Precision Min Word Level: 0.0
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+ - Recall Min Word Level: 0.0
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+ - F1 Min Word Level: 0.0
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+ - Precision Min Word Shift: 0.1429
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+ - Recall Min Word Shift: 0.125
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+ - F1 Min Word Shift: 0.1333
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - training_steps: 80000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | 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 |
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+ |:-------------:|:------:|:-----:|:---------------:|:--------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:|
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+ | No log | 0.0001 | 1 | 5.0835 | 121.5079 | 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 |
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+ | 0.0423 | 0.5167 | 10000 | 0.1010 | 13.7858 | 0.8705 | 0.8797 | 0.8745 | 0.8866 | 0.8961 | 0.8908 | 0.8899 | 0.8991 | 0.8939 | 0.9426 | 0.9519 | 0.9466 | 0.9286 | 0.9412 | 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 | 0.0 | 0.0 | 0.0 |
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+ | 0.0139 | 1.0334 | 20000 | 0.0950 | 10.6832 | 0.9090 | 0.9076 | 0.9079 | 0.9219 | 0.9205 | 0.9208 | 0.9251 | 0.9237 | 0.9239 | 0.9610 | 0.9611 | 0.9605 | 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 | 0.1111 | 0.125 |
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+ | 0.0089 | 1.5501 | 30000 | 0.0914 | 10.2458 | 0.9091 | 0.9077 | 0.9081 | 0.9208 | 0.9196 | 0.9198 | 0.9231 | 0.9220 | 0.9222 | 0.9596 | 0.9590 | 0.9589 | 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 | 0.1 | 0.125 | 0.1111 |
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+ | 0.0032 | 2.0668 | 40000 | 0.0922 | 9.3269 | 0.9163 | 0.9159 | 0.9157 | 0.9282 | 0.9279 | 0.9277 | 0.9307 | 0.9303 | 0.9301 | 0.9666 | 0.9676 | 0.9667 | 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 | 0.0909 | 0.1111 | 0.1176 |
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+ | 0.0025 | 2.5834 | 50000 | 0.0924 | 9.0500 | 0.9171 | 0.9179 | 0.9172 | 0.9283 | 0.9292 | 0.9284 | 0.9307 | 0.9314 | 0.9307 | 0.9656 | 0.9669 | 0.9659 | 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 |
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+ | 0.0022 | 3.1001 | 60000 | 0.0933 | 8.3137 | 0.9272 | 0.9266 | 0.9266 | 0.9377 | 0.9371 | 0.9371 | 0.9399 | 0.9393 | 0.9393 | 0.9702 | 0.9702 | 0.9698 | 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 |
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+ | 0.0006 | 3.6168 | 70000 | 0.0947 | 8.0682 | 0.9287 | 0.9302 | 0.9291 | 0.9393 | 0.9409 | 0.9398 | 0.9417 | 0.9430 | 0.9420 | 0.9706 | 0.9723 | 0.9710 | 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 |
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+ | 0.0002 | 4.1335 | 80000 | 0.0952 | 7.8511 | 0.9335 | 0.9352 | 0.9340 | 0.9440 | 0.9458 | 0.9446 | 0.9462 | 0.9479 | 0.9467 | 0.9714 | 0.9736 | 0.9721 | 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 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.2.1
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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