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End of training

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+ ---
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+ base_model: shhossain/whisper-tiny-bn-emo
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - audiofolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: whisper-tiny-bn-emo2024-05-16
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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: audiofolder
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+ type: audiofolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9759879350566723
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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-tiny-bn-emo2024-05-16
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+
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+ This model is a fine-tuned version of [shhossain/whisper-tiny-bn-emo](https://huggingface.co/shhossain/whisper-tiny-bn-emo) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0753
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+ - Accuracy: 0.9760
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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: 3e-05
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+ - train_batch_size: 32
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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: 128
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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: 5
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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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+ | 0.1554 | 1.0 | 331 | 0.1258 | 0.9614 |
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+ | 0.096 | 2.0 | 663 | 0.0973 | 0.9693 |
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+ | 0.1093 | 3.0 | 995 | 0.0854 | 0.9737 |
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+ | 0.0903 | 4.0 | 1327 | 0.0816 | 0.9743 |
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+ | 0.0676 | 4.99 | 1655 | 0.0753 | 0.9760 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.1
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.2