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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
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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-baset2
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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-baset2
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+
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+ This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0001
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+ - Wer: 1.9802
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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: 1
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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_steps: 100
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+ - training_steps: 1000
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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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+ | No log | 100.0 | 100 | 0.0009 | 1.9802 |
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+ | No log | 200.0 | 200 | 0.0003 | 1.9802 |
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+ | No log | 300.0 | 300 | 0.0002 | 1.9802 |
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+ | No log | 400.0 | 400 | 0.0001 | 1.9802 |
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+ | 0.0555 | 500.0 | 500 | 0.0001 | 1.9802 |
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+ | 0.0555 | 600.0 | 600 | 0.0001 | 1.9802 |
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+ | 0.0555 | 700.0 | 700 | 0.0001 | 1.9802 |
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+ | 0.0555 | 800.0 | 800 | 0.0001 | 1.9802 |
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+ | 0.0555 | 900.0 | 900 | 0.0001 | 1.9802 |
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+ | 0.0001 | 1000.0 | 1000 | 0.0001 | 1.9802 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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