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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-medium
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice_16_1
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: openai/whisper-medium
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: common_voice_16_1
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+ type: common_voice_16_1
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+ config: eu
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+ split: test
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+ args: eu
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 9.200601844614663
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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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+ # openai/whisper-medium
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+
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+ This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_16_1 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4303
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+ - Wer: 9.2006
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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: 64
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 256
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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: 500
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+ - training_steps: 40000
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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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+ | 0.0055 | 10.03 | 1000 | 0.2463 | 11.8425 |
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+ | 0.003 | 20.05 | 2000 | 0.2638 | 11.3178 |
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+ | 0.0018 | 30.08 | 3000 | 0.2837 | 10.9583 |
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+ | 0.0009 | 40.1 | 4000 | 0.2768 | 10.4414 |
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+ | 0.0008 | 50.13 | 5000 | 0.2880 | 10.1776 |
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+ | 0.0012 | 60.15 | 6000 | 0.2903 | 10.0526 |
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+ | 0.0002 | 70.18 | 7000 | 0.2909 | 9.8357 |
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+ | 0.0013 | 80.2 | 8000 | 0.2766 | 9.9392 |
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+ | 0.0001 | 90.23 | 9000 | 0.3110 | 9.3003 |
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+ | 0.0 | 100.25 | 10000 | 0.3278 | 9.3315 |
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+ | 0.0 | 110.28 | 11000 | 0.3393 | 9.3081 |
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+ | 0.0 | 120.3 | 12000 | 0.3508 | 9.2993 |
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+ | 0.0 | 130.33 | 13000 | 0.3617 | 9.3218 |
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+ | 0.0 | 140.35 | 14000 | 0.3732 | 9.3354 |
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+ | 0.0 | 150.38 | 15000 | 0.3849 | 9.3735 |
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+ | 0.0 | 160.4 | 16000 | 0.3073 | 9.3335 |
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+ | 0.0 | 170.43 | 17000 | 0.3320 | 9.3569 |
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+ | 0.0 | 180.45 | 18000 | 0.3453 | 9.3022 |
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+ | 0.0 | 190.48 | 19000 | 0.3561 | 9.3071 |
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+ | 0.0 | 200.5 | 20000 | 0.3660 | 9.2983 |
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+ | 0.0 | 210.53 | 21000 | 0.3755 | 9.2876 |
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+ | 0.0 | 220.55 | 22000 | 0.3847 | 9.4976 |
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+ | 0.0 | 230.58 | 23000 | 0.3940 | 9.5054 |
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+ | 0.0 | 240.6 | 24000 | 0.4021 | 9.4703 |
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+ | 0.0 | 250.63 | 25000 | 0.4126 | 9.4537 |
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+ | 0.0 | 260.65 | 26000 | 0.3174 | 9.2758 |
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+ | 0.0 | 270.68 | 27000 | 0.3444 | 9.2622 |
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+ | 0.0 | 280.7 | 28000 | 0.3588 | 9.2084 |
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+ | 0.0 | 290.73 | 29000 | 0.3698 | 9.3472 |
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+ | 0.0 | 300.75 | 30000 | 0.3786 | 9.3423 |
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+ | 0.0 | 310.78 | 31000 | 0.3868 | 9.3169 |
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+ | 0.0 | 320.8 | 32000 | 0.3948 | 9.3286 |
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+ | 0.0 | 330.83 | 33000 | 0.4018 | 9.3335 |
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+ | 0.0 | 340.85 | 34000 | 0.4081 | 9.3286 |
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+ | 0.0 | 350.88 | 35000 | 0.4138 | 9.3364 |
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+ | 0.0 | 360.9 | 36000 | 0.4191 | 9.3432 |
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+ | 0.0 | 370.93 | 37000 | 0.4234 | 9.3315 |
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+ | 0.0 | 380.95 | 38000 | 0.4270 | 9.3403 |
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+ | 0.0 | 390.98 | 39000 | 0.4294 | 9.2153 |
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+ | 0.0 | 401.0 | 40000 | 0.4303 | 9.2006 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 2.2.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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