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--- |
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language: |
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- en |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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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-large-cit-do1.5-wd1e-3-lr3 |
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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-large-cit-do1.5-wd1e-3-lr3 |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the SF 200 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9438 |
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- Wer: 33.1808 |
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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: 3e-06 |
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- train_batch_size: 4 |
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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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- gradient_accumulation_steps: 4 |
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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: 100 |
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- training_steps: 200 |
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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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| 1.087 | 0.8889 | 10 | 0.9839 | 39.8169 | |
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| 0.8784 | 1.7778 | 20 | 0.7808 | 34.3249 | |
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| 0.6585 | 2.6667 | 30 | 0.6338 | 32.2654 | |
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| 0.435 | 3.5556 | 40 | 0.5815 | 33.8673 | |
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| 0.3445 | 4.4444 | 50 | 0.5508 | 31.8078 | |
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| 0.2314 | 5.3333 | 60 | 0.5571 | 30.4348 | |
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| 0.1603 | 6.2222 | 70 | 0.5791 | 30.4348 | |
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| 0.0927 | 7.1111 | 80 | 0.6309 | 29.5195 | |
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| 0.0611 | 8.0 | 90 | 0.6768 | 32.7231 | |
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| 0.0366 | 8.8889 | 100 | 0.7544 | 29.7483 | |
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| 0.0199 | 9.7778 | 110 | 0.8286 | 30.8924 | |
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| 0.0155 | 10.6667 | 120 | 0.7920 | 29.5195 | |
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| 0.0066 | 11.5556 | 130 | 0.8726 | 30.2059 | |
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| 0.0054 | 12.4444 | 140 | 0.8955 | 31.3501 | |
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| 0.0077 | 13.3333 | 150 | 0.9194 | 32.0366 | |
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| 0.0076 | 14.2222 | 160 | 0.9336 | 32.4943 | |
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| 0.0021 | 15.1111 | 170 | 0.9399 | 33.1808 | |
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| 0.002 | 16.0 | 180 | 0.9404 | 32.2654 | |
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| 0.003 | 16.8889 | 190 | 0.9399 | 32.9519 | |
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| 0.0018 | 17.7778 | 200 | 0.9438 | 33.1808 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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