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--- |
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library_name: transformers |
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language: |
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- am |
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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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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: ' Medium Amharic - Biniyam Daniel' |
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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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# Medium Amharic - Biniyam Daniel |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0532 |
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- Wer: 19.1091 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:-----:|:---------------:|:-------:| |
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| 0.1306 | 0.0741 | 1000 | 0.1286 | 35.3980 | |
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| 0.0923 | 0.1482 | 2000 | 0.0923 | 26.9373 | |
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| 0.0742 | 0.2224 | 3000 | 0.0797 | 23.8271 | |
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| 0.0727 | 0.2965 | 4000 | 0.0748 | 23.6953 | |
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| 0.0706 | 0.3706 | 5000 | 0.0708 | 22.7201 | |
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| 0.0614 | 0.4447 | 6000 | 0.0689 | 22.0611 | |
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| 0.065 | 0.5189 | 7000 | 0.0671 | 21.5340 | |
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| 0.0594 | 0.5930 | 8000 | 0.0640 | 21.1650 | |
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| 0.0563 | 0.6671 | 9000 | 0.0619 | 21.1386 | |
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| 0.06 | 0.7412 | 10000 | 0.0618 | 21.1650 | |
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| 0.055 | 0.8153 | 11000 | 0.0597 | 20.6378 | |
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| 0.0558 | 0.8895 | 12000 | 0.0595 | 20.6115 | |
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| 0.0513 | 0.9636 | 13000 | 0.0584 | 19.8208 | |
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| 0.0521 | 1.0377 | 14000 | 0.0567 | 20.2161 | |
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| 0.0482 | 1.1118 | 15000 | 0.0567 | 20.0316 | |
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| 0.0458 | 1.1859 | 16000 | 0.0563 | 19.9789 | |
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| 0.0487 | 1.2600 | 17000 | 0.0559 | 19.7153 | |
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| 0.0448 | 1.3341 | 18000 | 0.0554 | 19.7417 | |
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| 0.0411 | 1.4083 | 19000 | 0.0553 | 19.4254 | |
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| 0.0407 | 1.4824 | 20000 | 0.0542 | 19.2145 | |
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| 0.0455 | 1.5565 | 21000 | 0.0539 | 19.1355 | |
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| 0.0439 | 1.6306 | 22000 | 0.0537 | 18.8719 | |
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| 0.0427 | 1.7048 | 23000 | 0.0538 | 19.2936 | |
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| 0.0389 | 1.7789 | 24000 | 0.0534 | 18.9773 | |
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| 0.0385 | 1.8530 | 25000 | 0.0533 | 19.0828 | |
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| 0.0366 | 1.9271 | 26000 | 0.0532 | 19.1091 | |
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### Framework versions |
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- Transformers 4.57.3 |
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- Pytorch 2.7.1+cu128 |
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- Datasets 3.6.0 |
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- Tokenizers 0.22.1 |
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