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Teamim-large-v2_Random-True_Augmented_date-26-06-2024_10-34-39

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 +100 -0
  2. generation_config.json +318 -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/Jun26_10-41-00_d25f8e1e1a05/events.out.tfevents.1719398461.d25f8e1e1a05.1.0 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: openai/whisper-large-v2
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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_Random-True_Augmented_date-26-06-2024_10-34-39
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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_Random-True_Augmented_date-26-06-2024_10-34-39
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+
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+ This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1042
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+ - Wer: 11.7960
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+ - Avg Precision Exact: 0.9096
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+ - Avg Recall Exact: 0.9088
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+ - Avg F1 Exact: 0.9088
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+ - Avg Precision Letter Shift: 0.9281
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+ - Avg Recall Letter Shift: 0.9274
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+ - Avg F1 Letter Shift: 0.9274
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+ - Avg Precision Word Level: 0.9303
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+ - Avg Recall Word Level: 0.9298
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+ - Avg F1 Word Level: 0.9297
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+ - Avg Precision Word Shift: 0.9743
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+ - Avg Recall Word Shift: 0.9743
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+ - Avg F1 Word Shift: 0.9739
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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: 0.1
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+ - F1 Min Word Shift: 0.1176
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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: 50
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+ - training_steps: 8000
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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 | 8e-05 | 1 | 5.8860 | 117.0584 | 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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+ | 0.1314 | 0.08 | 1000 | 0.1577 | 22.1766 | 0.8258 | 0.8234 | 0.8238 | 0.8536 | 0.8516 | 0.8518 | 0.8571 | 0.8560 | 0.8558 | 0.9351 | 0.9372 | 0.9352 | 0.9091 | 0.9 | 0.9 | 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 |
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+ | 0.0929 | 0.16 | 2000 | 0.1322 | 18.0894 | 0.8613 | 0.8621 | 0.8611 | 0.8856 | 0.8866 | 0.8855 | 0.8888 | 0.8901 | 0.8888 | 0.9503 | 0.9528 | 0.9508 | 0.9231 | 0.9231 | 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 | 0.1111 | 0.125 |
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+ | 0.0402 | 0.24 | 3000 | 0.1180 | 15.3622 | 0.8830 | 0.8851 | 0.8835 | 0.9048 | 0.9071 | 0.9055 | 0.9080 | 0.9104 | 0.9087 | 0.9617 | 0.9655 | 0.9631 | 0.9333 | 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 |
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+ | 0.0372 | 0.32 | 4000 | 0.1094 | 14.3792 | 0.8904 | 0.8894 | 0.8894 | 0.9141 | 0.9132 | 0.9131 | 0.9170 | 0.9162 | 0.9161 | 0.9680 | 0.9686 | 0.9677 | 0.9375 | 0.9412 | 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 | 0.1 | 0.1176 |
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+ | 0.0256 | 0.4 | 5000 | 0.1081 | 13.3518 | 0.9001 | 0.8983 | 0.8987 | 0.9198 | 0.9181 | 0.9185 | 0.9224 | 0.9211 | 0.9213 | 0.9710 | 0.9710 | 0.9705 | 1.0 | 1.0 | 0.9655 | 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 |
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+ | 0.0211 | 0.48 | 6000 | 0.1029 | 12.5203 | 0.9063 | 0.9046 | 0.9050 | 0.9261 | 0.9245 | 0.9249 | 0.9281 | 0.9269 | 0.9271 | 0.9713 | 0.9714 | 0.9709 | 1.0 | 1.0 | 0.9677 | 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 | 0.1111 |
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+ | 0.0096 | 0.56 | 7000 | 0.1043 | 11.8699 | 0.9097 | 0.9091 | 0.9090 | 0.9284 | 0.9279 | 0.9277 | 0.9305 | 0.9304 | 0.9300 | 0.9731 | 0.9738 | 0.9730 | 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 |
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+ | 0.0108 | 0.64 | 8000 | 0.1042 | 11.7960 | 0.9096 | 0.9088 | 0.9088 | 0.9281 | 0.9274 | 0.9274 | 0.9303 | 0.9298 | 0.9297 | 0.9743 | 0.9743 | 0.9739 | 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 |
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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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