End of training
Browse files- README.md +80 -0
- pytorch_model.bin +1 -1
README.md
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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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- marsyas/gtzan
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metrics:
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- accuracy
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model-index:
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- name: distilhubert-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: 0.74
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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-gtzan
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8432
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- Accuracy: 0.74
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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: 5
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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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| 1.9055 | 1.0 | 113 | 1.7174 | 0.46 |
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| 1.3089 | 2.0 | 226 | 1.2256 | 0.7 |
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| 1.0414 | 3.0 | 339 | 1.0002 | 0.71 |
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| 0.9251 | 4.0 | 452 | 0.9033 | 0.75 |
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| 0.9292 | 5.0 | 565 | 0.8432 | 0.74 |
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### Framework versions
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- Transformers 4.33.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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-
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size 94783376
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version https://git-lfs.github.com/spec/v1
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oid sha256:be536da558472d8fb916e22d6546496e2f9fd8f0e7754b2d2ec3341e9c56846e
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size 94783376
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