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--- |
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language: |
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- he |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: he |
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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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# he |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0736 |
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- Precision: 0.4148 |
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- Recall: 0.4107 |
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- F1: 0.4125 |
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- Precision Median: 0.0 |
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- Recall Median: 0.0 |
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- F1 Median: 0.0 |
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- Precision Max: 1.0 |
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- Recall Max: 1.0 |
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- F1 Max: 1.0 |
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- Precision Min: 0.0 |
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- Recall Min: 0.0 |
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- F1 Min: 0.0 |
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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: 8 |
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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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- training_steps: 4000 |
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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 | Precision | Recall | F1 | Precision Median | Recall Median | F1 Median | Precision Max | Recall Max | F1 Max | Precision Min | Recall Min | F1 Min | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:----------------:|:-------------:|:---------:|:-------------:|:----------:|:------:|:-------------:|:----------:|:------:| |
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| 0.0445 | 0.4 | 1000 | 0.0839 | 0.2598 | 0.2539 | 0.2566 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0203 | 0.79 | 2000 | 0.0686 | 0.5017 | 0.4976 | 0.4993 | 0.6667 | 0.6667 | 0.6667 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
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| 0.013 | 1.19 | 3000 | 0.0723 | 0.3647 | 0.3629 | 0.3635 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0016 | 1.58 | 4000 | 0.0736 | 0.4148 | 0.4107 | 0.4125 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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