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README.md
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---
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library_name: transformers
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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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metrics:
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- accuracy
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model-index:
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- name: distilhubert-HuBERT_Distilled
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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-HuBERT_Distilled
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2017
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- Accuracy: 0.8174
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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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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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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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| 1.4343 | 1.0 | 874 | 1.4833 | 0.5037 |
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| 0.8613 | 2.0 | 1748 | 0.9254 | 0.7081 |
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| 0.6081 | 3.0 | 2622 | 0.8306 | 0.7424 |
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| 0.7287 | 4.0 | 3496 | 0.8770 | 0.7453 |
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| 0.208 | 5.0 | 4370 | 0.8191 | 0.7831 |
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| 0.1136 | 6.0 | 5244 | 0.9336 | 0.7894 |
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| 0.094 | 7.0 | 6118 | 1.0803 | 0.7997 |
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| 0.0007 | 8.0 | 6992 | 1.1537 | 0.8122 |
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| 0.0649 | 9.0 | 7866 | 1.2157 | 0.8077 |
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| 0.0003 | 10.0 | 8740 | 1.2017 | 0.8174 |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.5.1+cu121
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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