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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_DropOut-0.3_WeightDecay-1e-05_Augmented_date-26-06-2024_22-25-46 |
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results: [] |
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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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# Teamim-large-v2_Random-True_DropOut-0.3_WeightDecay-1e-05_Augmented_date-26-06-2024_22-25-46 |
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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: 0.1039 |
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- Wer: 11.7812 |
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- Avg Precision Exact: 0.9060 |
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- Avg Recall Exact: 0.9051 |
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- Avg F1 Exact: 0.9052 |
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- Avg Precision Letter Shift: 0.9250 |
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- Avg Recall Letter Shift: 0.9242 |
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- Avg F1 Letter Shift: 0.9242 |
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- Avg Precision Word Level: 0.9276 |
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- Avg Recall Word Level: 0.9270 |
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- Avg F1 Word Level: 0.9269 |
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- Avg Precision Word Shift: 0.9735 |
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- Avg Recall Word Shift: 0.9738 |
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- Avg F1 Word Shift: 0.9732 |
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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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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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### Training results |
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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 | 5.7633 | 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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| 0.1301 | 0.08 | 1000 | 0.1621 | 22.8271 | 0.8134 | 0.8185 | 0.8150 | 0.8421 | 0.8478 | 0.8440 | 0.8463 | 0.8533 | 0.8488 | 0.9240 | 0.9351 | 0.9284 | 0.9 | 0.9 | 0.8966 | 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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| 0.0926 | 0.16 | 2000 | 0.1298 | 17.9675 | 0.8521 | 0.8555 | 0.8532 | 0.8767 | 0.8802 | 0.8778 | 0.8803 | 0.8838 | 0.8814 | 0.9476 | 0.9528 | 0.9495 | 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 | 0.0 | 0.0 | 0.0 | |
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| 0.0393 | 0.24 | 3000 | 0.1162 | 15.4250 | 0.8854 | 0.8838 | 0.8841 | 0.9067 | 0.9055 | 0.9055 | 0.9096 | 0.9089 | 0.9087 | 0.9643 | 0.9651 | 0.9641 | 0.9375 | 0.9375 | 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 | 0.1 | 0.1176 | |
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| 0.0345 | 0.32 | 4000 | 0.1122 | 14.0946 | 0.8904 | 0.8905 | 0.8900 | 0.9124 | 0.9125 | 0.9120 | 0.9155 | 0.9164 | 0.9155 | 0.9657 | 0.9678 | 0.9662 | 0.9412 | 0.9412 | 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 | 0.1 | 0.1176 | |
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| 0.0264 | 0.4 | 5000 | 0.1077 | 12.7827 | 0.9002 | 0.9017 | 0.9005 | 0.9194 | 0.9210 | 0.9197 | 0.9216 | 0.9237 | 0.9222 | 0.9692 | 0.9720 | 0.9701 | 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 | 0.125 | 0.125 | 0.1333 | |
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| 0.0247 | 0.48 | 6000 | 0.1036 | 12.6829 | 0.9002 | 0.9013 | 0.9004 | 0.9198 | 0.9211 | 0.9200 | 0.9222 | 0.9238 | 0.9226 | 0.9703 | 0.9731 | 0.9712 | 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 | 0.1429 | 0.1 | 0.1176 | |
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| 0.0115 | 0.56 | 7000 | 0.1045 | 12.0103 | 0.9035 | 0.9036 | 0.9032 | 0.9230 | 0.9231 | 0.9226 | 0.9256 | 0.9262 | 0.9255 | 0.9721 | 0.9732 | 0.9722 | 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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| 0.0123 | 0.64 | 8000 | 0.1039 | 11.7812 | 0.9060 | 0.9051 | 0.9052 | 0.9250 | 0.9242 | 0.9242 | 0.9276 | 0.9270 | 0.9269 | 0.9735 | 0.9738 | 0.9732 | 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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### Framework versions |
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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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