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--- |
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license: apache-2.0 |
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base_model: ntu-spml/distilhubert |
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tags: |
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- generated_from_trainer |
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datasets: |
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- thisisjibon/banglabeats |
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metrics: |
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- accuracy |
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model-index: |
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- name: distilhubert-finetuned-banglabeats |
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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: BanglaBeats |
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type: thisisjibon/banglabeats |
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config: all |
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split: train |
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args: all |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8336425479282622 |
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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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# distilhubert-finetuned-banglabeats |
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the BanglaBeats dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4126 |
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- Accuracy: 0.8336 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 0.9439 | 1.0 | 910 | 0.9274 | 0.6425 | |
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| 0.854 | 2.0 | 1820 | 0.7498 | 0.7260 | |
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| 0.4835 | 3.0 | 2730 | 0.6329 | 0.7706 | |
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| 0.6226 | 4.0 | 3640 | 0.6159 | 0.7934 | |
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| 0.456 | 5.0 | 4550 | 0.7118 | 0.7972 | |
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| 0.0565 | 6.0 | 5460 | 0.7994 | 0.8052 | |
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| 0.2605 | 7.0 | 6370 | 0.9735 | 0.8151 | |
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| 0.3635 | 8.0 | 7280 | 1.0618 | 0.8244 | |
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| 0.1879 | 9.0 | 8190 | 1.1644 | 0.8213 | |
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| 0.0292 | 10.0 | 9100 | 1.2543 | 0.8194 | |
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| 0.0002 | 11.0 | 10010 | 1.4084 | 0.8101 | |
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| 0.0006 | 12.0 | 10920 | 1.3823 | 0.8132 | |
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| 0.088 | 13.0 | 11830 | 1.4016 | 0.8256 | |
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| 0.0381 | 14.0 | 12740 | 1.3587 | 0.8225 | |
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| 0.0 | 15.0 | 13650 | 1.4242 | 0.8169 | |
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| 0.0 | 16.0 | 14560 | 1.4053 | 0.8275 | |
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| 0.0183 | 17.0 | 15470 | 1.4357 | 0.8318 | |
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| 0.0 | 18.0 | 16380 | 1.4123 | 0.8306 | |
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| 0.0098 | 19.0 | 17290 | 1.4077 | 0.8330 | |
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| 0.0 | 20.0 | 18200 | 1.4126 | 0.8336 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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