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--- |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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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-base-finetuned2222222222222222222222222222222 |
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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-finetuned2222222222222222222222222222222 |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0018 |
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- Wer: 0.125 |
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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-06 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: 5 |
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- training_steps: 400 |
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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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| 7.7056 | 0.8 | 20 | 6.4502 | 16.25 | |
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| 4.7836 | 1.6 | 40 | 2.9149 | 10.375 | |
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| 1.8399 | 2.4 | 60 | 0.8254 | 7.875 | |
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| 0.3132 | 3.2 | 80 | 0.0852 | 3.875 | |
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| 0.0335 | 4.0 | 100 | 0.0190 | 1.7500 | |
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| 0.0067 | 4.8 | 120 | 0.0080 | 1.0 | |
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| 0.0032 | 5.6 | 140 | 0.0050 | 0.375 | |
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| 0.0021 | 6.4 | 160 | 0.0039 | 0.125 | |
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| 0.0017 | 7.2 | 180 | 0.0034 | 0.125 | |
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| 0.0015 | 8.0 | 200 | 0.0030 | 0.125 | |
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| 0.0013 | 8.8 | 220 | 0.0027 | 0.125 | |
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| 0.0012 | 9.6 | 240 | 0.0025 | 0.125 | |
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| 0.0011 | 10.4 | 260 | 0.0023 | 0.125 | |
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| 0.001 | 11.2 | 280 | 0.0021 | 0.125 | |
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| 0.0009 | 12.0 | 300 | 0.0020 | 0.125 | |
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| 0.0009 | 12.8 | 320 | 0.0020 | 0.125 | |
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| 0.0009 | 13.6 | 340 | 0.0019 | 0.125 | |
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| 0.0008 | 14.4 | 360 | 0.0018 | 0.125 | |
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| 0.0009 | 15.2 | 380 | 0.0018 | 0.125 | |
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| 0.0008 | 16.0 | 400 | 0.0018 | 0.125 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.15.2 |
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