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README.md ADDED
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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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+
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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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+
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+ # whisper-large-v3-atco2-asr
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+
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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 None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7695
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+ - Wer: 17.0374
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|
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+ | 0.1388 | 3.57 | 100 | 0.5488 | 20.1957 |
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+ | 0.0313 | 7.14 | 200 | 0.5830 | 17.5712 |
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+ | 0.0173 | 10.71 | 300 | 0.5898 | 20.4181 |
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+ | 0.004 | 14.29 | 400 | 0.6201 | 16.3256 |
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+ | 0.001 | 17.86 | 500 | 0.6543 | 18.4164 |
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+ | 0.002 | 21.43 | 600 | 0.6499 | 17.8381 |
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+ | 0.0003 | 25.0 | 700 | 0.6724 | 17.1263 |
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+ | 0.0002 | 28.57 | 800 | 0.6890 | 16.9929 |
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+ | 0.0002 | 32.14 | 900 | 0.7012 | 16.8594 |
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+ | 0.0001 | 35.71 | 1000 | 0.7104 | 16.9484 |
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+ | 0.0001 | 39.29 | 1100 | 0.7178 | 16.9039 |
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+ | 0.0001 | 42.86 | 1200 | 0.7241 | 17.4377 |
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+ | 0.0001 | 46.43 | 1300 | 0.7305 | 17.3488 |
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+ | 0.0001 | 50.0 | 1400 | 0.7358 | 17.3043 |
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+ | 0.0001 | 53.57 | 1500 | 0.7407 | 17.3043 |
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+ | 0.0001 | 57.14 | 1600 | 0.7451 | 17.1263 |
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+ | 0.0001 | 60.71 | 1700 | 0.7495 | 17.2598 |
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+ | 0.0001 | 64.29 | 1800 | 0.7529 | 17.2153 |
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+ | 0.0001 | 67.86 | 1900 | 0.7563 | 17.2598 |
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+ | 0.0001 | 71.43 | 2000 | 0.7593 | 17.4377 |
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+ | 0.0001 | 75.0 | 2100 | 0.7612 | 17.3932 |
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+ | 0.0001 | 78.57 | 2200 | 0.7632 | 17.2598 |
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+ | 0.0 | 82.14 | 2300 | 0.7651 | 17.1263 |
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+ | 0.0 | 85.71 | 2400 | 0.7666 | 17.0819 |
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+ | 0.0 | 89.29 | 2500 | 0.7681 | 17.0374 |
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+ | 0.0 | 92.86 | 2600 | 0.7686 | 17.0374 |
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+ | 0.0 | 96.43 | 2700 | 0.7695 | 17.1263 |
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+ | 0.0 | 100.0 | 2800 | 0.7695 | 17.0374 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.12.0
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+ - Tokenizers 0.14.1
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