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--- |
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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-final |
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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-final |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0714 |
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- Wer: 6.3947 |
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## Model description |
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Step Training Loss Validation Loss Wer |
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1000 0.727300 0.734777 71.347666 |
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2000 0.392000 0.430395 52.059163 |
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3000 0.317100 0.305939 39.781162 |
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4000 0.206400 0.225029 30.785726 |
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5000 0.152800 0.169434 23.076923 |
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6000 0.119000 0.130408 16.517293 |
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7000 0.082300 0.102279 11.755650 |
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8000 0.079600 0.085155 8.511574 |
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9000 0.051400 0.075068 7.048991 |
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10000 0.045000 0.071429 6.394678 |
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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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- 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: 1000 |
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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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| 0.7273 | 1.6051 | 1000 | 0.7348 | 71.3477 | |
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| 0.392 | 3.2103 | 2000 | 0.4304 | 52.0592 | |
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| 0.3171 | 4.8154 | 3000 | 0.3059 | 39.7812 | |
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| 0.2064 | 6.4205 | 4000 | 0.2250 | 30.7857 | |
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| 0.1528 | 8.0257 | 5000 | 0.1694 | 23.0769 | |
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| 0.119 | 9.6308 | 6000 | 0.1304 | 16.5173 | |
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| 0.0823 | 11.2360 | 7000 | 0.1023 | 11.7556 | |
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| 0.0796 | 12.8411 | 8000 | 0.0852 | 8.5116 | |
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| 0.0514 | 14.4462 | 9000 | 0.0751 | 7.0490 | |
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| 0.045 | 16.0514 | 10000 | 0.0714 | 6.3947 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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