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README.md ADDED
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+ ---
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+ library_name: transformers
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+ language:
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+ - ac
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+ license: apache-2.0
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+ base_model: openai/whisper-small
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+ tags:
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+ - whisper-event
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+ - generated_from_trainer
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+ datasets:
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+ - tericlabs
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper base acholi
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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: Sunbird_salt
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+ type: tericlabs
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 125.91206735266604
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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 base acholi
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Sunbird_salt dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 6.3204
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+ - Wer: 125.9121
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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: 32
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 1000
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+ - training_steps: 20000
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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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+ | 3.9219 | 6.6225 | 1000 | 2.8840 | 196.1646 |
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+ | 2.2828 | 13.2450 | 2000 | 2.8298 | 129.9345 |
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+ | 1.399 | 19.8675 | 3000 | 3.3370 | 135.6408 |
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+ | 0.5689 | 26.4901 | 4000 | 3.9490 | 141.4406 |
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+ | 0.1519 | 33.1126 | 5000 | 4.4924 | 117.0253 |
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+ | 0.0408 | 39.7351 | 6000 | 4.8503 | 130.4958 |
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+ | 0.0176 | 46.3576 | 7000 | 5.1254 | 123.5734 |
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+ | 0.0101 | 52.9801 | 8000 | 5.2911 | 128.7184 |
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+ | 0.0049 | 59.6026 | 9000 | 5.5606 | 145.7437 |
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+ | 0.004 | 66.2252 | 10000 | 5.6918 | 131.7119 |
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+ | 0.003 | 72.8477 | 11000 | 5.8036 | 130.5893 |
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+ | 0.0021 | 79.4702 | 12000 | 5.9199 | 127.5023 |
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+ | 0.0008 | 86.0927 | 13000 | 6.0288 | 134.5182 |
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+ | 0.0021 | 92.7152 | 14000 | 6.0003 | 133.4892 |
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+ | 0.0006 | 99.3377 | 15000 | 6.1112 | 123.0122 |
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+ | 0.0003 | 105.9603 | 16000 | 6.1775 | 122.1703 |
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+ | 0.0002 | 112.5828 | 17000 | 6.2225 | 125.6314 |
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+ | 0.0002 | 119.2053 | 18000 | 6.2691 | 126.3798 |
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+ | 0.0002 | 125.8278 | 19000 | 6.3077 | 125.7250 |
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+ | 0.0002 | 132.4503 | 20000 | 6.3204 | 125.9121 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.0.dev0
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 3.0.2
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+ - Tokenizers 0.20.1
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