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--- |
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library_name: transformers |
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language: |
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- spa |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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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: Whisper Tiny All Audios - vfranchis |
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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 Tiny All Audios - vfranchis |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the All audios 1.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0368 |
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- Wer: 1.9658 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 25 |
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- training_steps: 650 |
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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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| 1.4661 | 0.05 | 25 | 0.5654 | 20.5212 | |
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| 0.2642 | 0.1 | 50 | 0.1588 | 8.6859 | |
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| 0.1282 | 0.15 | 75 | 0.1102 | 6.3494 | |
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| 0.0861 | 0.2 | 100 | 0.0901 | 4.9068 | |
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| 0.0652 | 0.25 | 125 | 0.0784 | 4.0738 | |
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| 0.0676 | 0.3 | 150 | 0.0695 | 3.4490 | |
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| 0.0865 | 0.35 | 175 | 0.0649 | 3.4185 | |
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| 0.0454 | 0.4 | 200 | 0.0610 | 3.0477 | |
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| 0.0517 | 0.45 | 225 | 0.0567 | 2.9664 | |
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| 0.0471 | 0.5 | 250 | 0.0548 | 2.8344 | |
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| 0.0394 | 0.55 | 275 | 0.0521 | 2.8648 | |
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| 0.0347 | 0.6 | 300 | 0.0488 | 2.4585 | |
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| 0.0596 | 0.65 | 325 | 0.0477 | 2.4483 | |
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| 0.0426 | 0.7 | 350 | 0.0452 | 2.7836 | |
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| 0.0428 | 0.75 | 375 | 0.0436 | 2.2401 | |
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| 0.0518 | 0.8 | 400 | 0.0417 | 2.1181 | |
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| 0.0379 | 0.85 | 425 | 0.0407 | 2.0928 | |
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| 0.0259 | 0.9 | 450 | 0.0399 | 1.9861 | |
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| 0.0691 | 0.95 | 475 | 0.0394 | 2.2096 | |
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| 0.0382 | 1.0 | 500 | 0.0384 | 2.1131 | |
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| 0.0311 | 1.05 | 525 | 0.0377 | 1.9810 | |
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| 0.0301 | 1.1 | 550 | 0.0375 | 1.9404 | |
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| 0.021 | 1.15 | 575 | 0.0371 | 1.9505 | |
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| 0.0205 | 1.2 | 600 | 0.0369 | 1.9404 | |
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| 0.0163 | 1.25 | 625 | 0.0369 | 1.9505 | |
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| 0.018 | 1.3 | 650 | 0.0368 | 1.9658 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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