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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: distilhubert-finetuned-music-genres-small
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results: []
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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-music-genres-small
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6827
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- Accuracy: 0.4
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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: 5e-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: 5
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- mixed_precision_training: Native AMP
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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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| No log | 0.99 | 56 | 2.0784 | 0.36 |
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| 2.098 | 1.99 | 112 | 1.8533 | 0.35 |
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| 2.098 | 2.99 | 168 | 1.7524 | 0.39 |
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| 1.7241 | 3.99 | 224 | 1.6827 | 0.4 |
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| 1.7241 | 4.99 | 280 | 1.6565 | 0.39 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.11.0
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- Datasets 2.6.1
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- Tokenizers 0.11.6
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