End of training
Browse files- README.md +81 -0
- model.safetensors +1 -1
README.md
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---
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library_name: transformers
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base_model: DistilHuBERT
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tags:
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- generated_from_trainer
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datasets:
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- marsyas/gtzan
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metrics:
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- accuracy
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model-index:
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- name: HuBERT-Genre-Clf-finetuned-gtzan
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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: GTZAN
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type: marsyas/gtzan
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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: 0.92
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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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# HuBERT-Genre-Clf-finetuned-gtzan
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This model is a fine-tuned version of [DistilHuBERT](https://huggingface.co/DistilHuBERT) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3339
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- Accuracy: 0.92
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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: 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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| 0.1135 | 1.0 | 113 | 0.3252 | 0.93 |
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| 0.0176 | 2.0 | 226 | 0.3014 | 0.94 |
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| 0.0026 | 3.0 | 339 | 0.3110 | 0.95 |
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| 0.0015 | 4.0 | 452 | 0.4329 | 0.93 |
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| 0.0013 | 5.0 | 565 | 0.3339 | 0.92 |
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### Framework versions
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- Transformers 4.48.0.dev0
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- Pytorch 2.5.1+cu121
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
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size 94771728
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version https://git-lfs.github.com/spec/v1
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size 94771728
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