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--- |
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license: apache-2.0 |
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base_model: openai/whisper-base.en |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: whisper-base.en-fsc |
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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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# whisper-base.en-fsc |
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This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.0278 |
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- Accuracy: 0.5630 |
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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: 5e-05 |
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- train_batch_size: 48 |
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- eval_batch_size: 48 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 192 |
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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_ratio: 0.1 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| No log | 0.9972 | 263 | 3.7447 | 0.0962 | |
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| No log | 1.9981 | 527 | 2.8087 | 0.3060 | |
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| No log | 2.9991 | 791 | 2.3083 | 0.4062 | |
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| 2.9232 | 4.0 | 1055 | 2.0094 | 0.4940 | |
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| 2.9232 | 4.9972 | 1318 | 1.9099 | 0.5321 | |
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| 2.9232 | 5.9981 | 1582 | 1.9257 | 0.5479 | |
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| 2.9232 | 6.9991 | 1846 | 2.0132 | 0.5479 | |
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| 0.8199 | 8.0 | 2110 | 2.1486 | 0.5444 | |
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| 0.8199 | 8.9972 | 2373 | 2.2976 | 0.5440 | |
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| 0.8199 | 9.9981 | 2637 | 2.4131 | 0.5453 | |
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| 0.8199 | 10.9991 | 2901 | 2.5031 | 0.5523 | |
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| 0.1503 | 12.0 | 3165 | 2.6273 | 0.5544 | |
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| 0.1503 | 12.9972 | 3428 | 2.7233 | 0.5581 | |
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| 0.1503 | 13.9981 | 3692 | 2.8470 | 0.5498 | |
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| 0.1503 | 14.9991 | 3956 | 2.8848 | 0.5589 | |
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| 0.0246 | 16.0 | 4220 | 2.9497 | 0.5605 | |
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| 0.0246 | 16.9972 | 4483 | 2.9992 | 0.5612 | |
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| 0.0246 | 17.9981 | 4747 | 3.0278 | 0.5630 | |
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| 0.0043 | 18.9991 | 5011 | 3.0502 | 0.5629 | |
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| 0.0043 | 19.9431 | 5260 | 3.0561 | 0.5629 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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