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--- |
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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: windanam-whisper-medium |
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results: [] |
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language: |
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- ff |
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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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# windanam-whisper-medium |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the [cawoylel/FulaSpeechCorpora-splited-noise_augmented](https://huggingface.co/datasets/cawoylel/FulaSpeechCorpora-splited-noise_augmented) dataset. The finetuning was done on the train and test splits of the dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1407 |
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- Wer: 0.2006 |
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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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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 32 |
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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: 500 |
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- training_steps: 10000 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 0.5665 | 0.16 | 1000 | 0.3283 | 0.3337 | |
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| 0.3998 | 0.31 | 2000 | 0.2489 | 0.2825 | |
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| 0.35 | 0.47 | 3000 | 0.2061 | 0.2549 | |
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| 0.3084 | 0.62 | 4000 | 0.1842 | 0.2263 | |
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| 0.2603 | 0.78 | 5000 | 0.1693 | 0.2169 | |
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| 0.2414 | 0.93 | 6000 | 0.1592 | 0.2097 | |
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| 0.1604 | 1.09 | 7000 | 0.1519 | 0.2009 | |
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| 0.1584 | 1.24 | 8000 | 0.1474 | 0.2007 | |
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| 0.1442 | 1.4 | 9000 | 0.1427 | 0.1980 | |
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| 0.1391 | 1.55 | 10000 | 0.1407 | 0.2006 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
