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End of training

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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-base.en
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - speech_commands
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: whisper-base.en-speech-commands-h
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+ results:
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+ - task:
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+ name: Audio Classification
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+ type: audio-classification
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+ dataset:
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+ name: speech_commands
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+ type: speech_commands
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+ config: v0.02
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+ split: None
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+ args: v0.02
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.7922661870503597
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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.en-speech-commands-h
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+
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+ This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the speech_commands dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.3313
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+ - Accuracy: 0.7923
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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: 0.0005
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+ - train_batch_size: 96
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+ - eval_batch_size: 96
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+ - seed: 42
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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_ratio: 0.1
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+ - num_epochs: 20
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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 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.3859 | 1.0 | 412 | 1.3474 | 0.7707 |
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+ | 0.2732 | 2.0 | 824 | 1.2471 | 0.7599 |
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+ | 0.2373 | 3.0 | 1236 | 1.2114 | 0.7729 |
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+ | 0.1694 | 4.0 | 1648 | 1.1600 | 0.7914 |
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+ | 0.1495 | 5.0 | 2060 | 1.1535 | 0.7914 |
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+ | 0.1931 | 6.0 | 2472 | 1.1446 | 0.7860 |
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+ | 0.1329 | 7.0 | 2884 | 1.3313 | 0.7923 |
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+ | 0.0731 | 8.0 | 3296 | 1.2812 | 0.7860 |
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+ | 0.0702 | 9.0 | 3708 | 1.2134 | 0.7873 |
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+ | 0.0828 | 10.0 | 4120 | 1.6292 | 0.7887 |
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+ | 0.08 | 11.0 | 4532 | 1.4677 | 0.7797 |
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+ | 0.0481 | 12.0 | 4944 | 1.3770 | 0.7909 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.43.3
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+ - Pytorch 2.2.2+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.19.1
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