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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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datasets:
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- xbgoose/ravdess
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metrics:
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- accuracy
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model-index:
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- name: distilhubert-finetuned-ravdess
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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-ravdess
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the RAVDESS dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2810
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- Accuracy: 0.9236
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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: 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: 10
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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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| 1.7599 | 1.0 | 162 | 1.7350 | 0.3264 |
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| 1.3271 | 2.0 | 324 | 1.1987 | 0.5972 |
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| 0.8845 | 3.0 | 486 | 0.8824 | 0.7639 |
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| 0.6083 | 4.0 | 648 | 0.5919 | 0.8403 |
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| 0.4952 | 5.0 | 810 | 0.4469 | 0.8611 |
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| 0.1386 | 6.0 | 972 | 0.3736 | 0.8681 |
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| 0.1028 | 7.0 | 1134 | 0.3645 | 0.8819 |
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| 0.053 | 8.0 | 1296 | 0.3079 | 0.9028 |
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| 0.0149 | 9.0 | 1458 | 0.2723 | 0.9236 |
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| 0.0154 | 10.0 | 1620 | 0.2810 | 0.9236 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.0
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- Datasets 2.13.0
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- Tokenizers 0.13.3
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