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--- |
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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-v3-atco2-asr |
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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-v3-atco2-asr |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7578 |
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- Wer: 29.0480 |
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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: 16 |
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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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- 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: 2800 |
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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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| 0.1323 | 3.57 | 100 | 0.5386 | 20.4626 | |
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| 0.0207 | 7.14 | 200 | 0.5952 | 40.3025 | |
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| 0.0125 | 10.71 | 300 | 0.5767 | 25.9342 | |
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| 0.0056 | 14.29 | 400 | 0.6133 | 20.6406 | |
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| 0.0022 | 17.86 | 500 | 0.6367 | 30.2936 | |
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| 0.0005 | 21.43 | 600 | 0.6670 | 21.6637 | |
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| 0.0002 | 25.0 | 700 | 0.6841 | 22.2420 | |
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| 0.0002 | 28.57 | 800 | 0.6948 | 23.4431 | |
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| 0.0001 | 32.14 | 900 | 0.7026 | 23.6210 | |
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| 0.0001 | 35.71 | 1000 | 0.7095 | 26.0676 | |
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| 0.0001 | 39.29 | 1100 | 0.7153 | 25.9786 | |
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| 0.0001 | 42.86 | 1200 | 0.7202 | 25.1335 | |
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| 0.0001 | 46.43 | 1300 | 0.7251 | 25.3559 | |
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| 0.0001 | 50.0 | 1400 | 0.7295 | 29.4929 | |
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| 0.0001 | 53.57 | 1500 | 0.7334 | 25.9786 | |
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| 0.0001 | 57.14 | 1600 | 0.7373 | 28.6032 | |
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| 0.0001 | 60.71 | 1700 | 0.7402 | 28.9146 | |
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| 0.0 | 64.29 | 1800 | 0.7427 | 29.4484 | |
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| 0.0001 | 67.86 | 1900 | 0.7461 | 29.4484 | |
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| 0.0 | 71.43 | 2000 | 0.7480 | 32.2509 | |
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| 0.0 | 75.0 | 2100 | 0.7505 | 32.2064 | |
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| 0.0001 | 78.57 | 2200 | 0.7524 | 32.2064 | |
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| 0.0 | 82.14 | 2300 | 0.7539 | 32.2509 | |
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| 0.0 | 85.71 | 2400 | 0.7549 | 32.3843 | |
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| 0.0 | 89.29 | 2500 | 0.7563 | 32.2954 | |
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| 0.0 | 92.86 | 2600 | 0.7573 | 32.3399 | |
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| 0.0 | 96.43 | 2700 | 0.7578 | 29.0480 | |
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| 0.0 | 100.0 | 2800 | 0.7578 | 29.0480 | |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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